My name is Eugene Kelly. I'm a professor of pedology in the Department of Soil and Crop Sciences at Colorado State University. And our discussion today is going to center on soils and more specifically soil landscape relationships. What I'd like to do is to present this topic through the eyes of a pedologist. And our pedologist is somebody who studies soils and soil formation under different types of environmental conditions. And by doing so, in other words, understanding how soils form, we develop the capacity to predict how soils will behave when environmental conditions change. More specifically, I'll be looking at soil formation and soil properties as a function of landscape and topographic variations. Now, based on years of research in pedology and soil science, there are two fundamental things we know about soils. That soils first reflect environmental conditions and they also affect environmental conditions. This is called the duality of soil science. In other words, a soil reflects the environmental conditions under which it evolved. And that includes the climatological, geological, biological, and topographical conditions that generally define the state of the soil system. Secondly, soils affect the environment through the properties that are intrinsically native to the soil, again resulting from soil formation. These properties mitigate things like gas exchange, water content, and nutrient status and have a profound influence on the development of the soil and the ecosystem, and ultimately the productivity in natural and agricultural settings. So the soils of any region reflect environmental conditions, but they also affect environmental conditions. Now, as a pedologist, what we're going to do, we're going to study three basic components of pedology that will allow us to make this assessment of soils and environmental conditions as a function of topographic variations. What we're going to talk about first are the factors of soil formation, and then secondly, we'll talk about soil forming processes, or we refer to them as soil processes, and then finally we'll touch on some of the key soil properties. So we'll be talking about factors, processes, and properties. Understanding the relationship among the three of those groups is critical to evaluating soils through the eyes of a pedologist. First, we're going to discuss soil formation and the factors of soil formation. The factors of soil formation were first formalized by Han Jenny in his text in 1941. The text was entitled The Factors of Soil Formation. Now in this text, what Jenny did was he conceptually evaluated the mathematical relationships between soil properties and soils and what he considered to be controlling variables or conditioning variables. He later referred to these as state factors. He developed mathematical expressions that allowed any scientist or any person for that matter to evaluate soil properties in the context of these conditioning variables. In the text, Jenny expresses a mathematical relationship between soil and what he considers to be the state factors of soil formation. There is follows. The soil is a function of the climate, the organisms, the relief, the parent material, and time. And they're all symbolically expressed in this equation. The equation allows us to assess the variation in any of these conditioning variables and its impact on any specific soil property or ecosystem property for that matter. Now the application of the state factor theory is something we're going to address in the first part of this lecture. And what I would like to do is to kind of explain how this approach works. Essentially what you need to do is you need to assess a soil or soil property as a function of one of the conditioning variables. For example, climatological variables might be something like precipitation or temperature. Biological variables might be grasslands versus forests. So the equation allows one to assess the impact of any of these conditioning variables on a single soil property. So for the example that I'm going to use in this discussion, we'll be looking at soil, organic, carbon content. And we'll be looking at soil, organic, carbon content as a function of each of these conditioning variables basically to assess what the state of the soil system is. Now the first example I'm going to run through is looking at soil, organic, carbon, or what's just for that matter, let's just say soil as a function of climatic conditions. In the equation we see soil as a function of climate. And you'll note that the other variables are held inactive or relatively constant. Essentially what you need to do is you need to isolate the climatic variable, evaluate a soil property, and then vary climate to see what the impact of climate is on a specific soil property. For the examples, again, what I'll be doing is I'll be going through an evaluation of soil, organic, carbon accumulation as a function of each of the state factors. This equation expresses the soil, carbon, as a function of climatic variations. This is referred to as a climosequence. Now the first schematic shows us soil, organic, carbon content as a function of mean annual precipitation. And there are three platelets dealing with different soil textures. You'll note the platelet to the left looks at clay soils, the middle platelet looks at loam soils, and the platelet to the right looks at sandy soils. The relationships that are important here are as follows. If you'll note that organic, carbon content increases with increasing mean annual precipitation. In the first platelet, the clay soil, we see increasing carbon content with increasing mean annual precipitation. In a similar fashion, we see the same relationship with loam soils and with the sandy soils, increasing carbon content with increasing mean annual precipitation. Now in order to do this assessment, what you would need to do was to find soils within the same climatic region that varied as a function of texture and then move across precipitation gradients and evaluate the carbon content of these systems. Another observation of these data is that we look at rangelands versus cultivated in the same climatic regimes. In other words, evaluating clay soils that are under rangeland conditions versus clay soils that are under cultivated conditions. What you'll note is that both, in both systems, carbon content increases as a function of increasing precipitation. What's interesting to note is that this relationship occurs in the clay soils, the loam soils and in the sandy soils, but there appears to be a difference between rangeland systems and cultivated systems. This is an assessment of human impacts on soil formation and that is generally understood that cultivation induces carbon loss in most natural systems. So to note, we see the same increase in carbon content regardless of soil texture. This is an example of how climate conditions carbon content of soil. Again, all the other state factors in this example have been kept constant and these are data that are adapted from Burke in 1989. The other thing to note is that you'll see that the sandy soil has the lowest carbon content overall and the clay soils have the highest carbon content. The next example from Yanny's model is to look at a bio sequence. In this particular example, what we'll be looking at is the variations in vegetation type and the properties that they impart on the system, specifically again looking at soil carbon. On the Y axis, what we see is soil depth in centimeters and on the X axis, we see organic carbon content again in kilograms per square meter for three different systems. You'll note that the system to the left deals with short grass step vegetation and has about 5.7 kilograms per cubic meter of carbon. The Lodge pole pine system, the second platelet, has 4.8 kilograms per cubic meter and the alpine tundra has 18.1 kilograms per cubic meter. A very large difference in the amount of carbon stored in each of these systems as produced by different vegetation types. This is referred to as a bio sequence. In other words, the vegetation has a specific role in determining how much carbon is stored in the system. Now, if we take a closer look at these data, we see that the carbon content in the alpine tundra system is very high in a near surface environment and this is very typical of soils that we see worldwide. Carbon content generally decreases with increasing depth in the soil. The differences within the soil profiles in the short grass step and Lodge pole are not as dramatic. What we also notice is that the differences in the vegetation types impart very large differences in the total carbon stored. Much of this is related to the morphology of the plants. For example, in a short grass step ecosystem, we understand that at least half of the biomass is below ground, which would allow us to have more carbon storage in that particular system. In contrast, the system in Lodge pole pine has much of the biomass above ground, again resulting in lower carbon content in the soil, a relationship that's pretty clearly understood in Colorado for that matter. But the alpine tundra system is very, very different and that most of the biomass in this system is below ground, thus resulting in increased carbon content relative to most of the systems we observe in the Rocky Mountain region. The next example of any state factor approach we'll be looking at what we refer to as a lithosequence. In this particular case, we vary the parent material or the geologic substrate under which soil formation occurred and again we're going to evaluate soil carbon content. Now in this example, adapted from Aguilar in 1984, we evaluate three different parent material types sandstone, siltstone, and shales. And generally what we're doing is we're keeping all the other state factors inactive or constant. In other words, topographic variations are minimized, climatic variations are minimized, vegetation variations are minimized, and the time of soil formation is minimized. So what we're evaluating is the influence of parent material on soil organic carbon storage for three sites. What you'll note is that the shale site has the most organic carbon relative to the siltstone and the sandstone sites. You'll notice again that there's variation in carbon content within the soil profiles as a function of depth. In each and every system carbon content is highest near the surface and decreases with increasing depth. What you'll note and what's interesting in these particular data is that our most productive rangeland sites are actually the sandstone sites and they have the lowest amount of carbon storage. These types of relationships will be discussed later when we talk about processes that are important to carbon storage and systems. Another example of any state factor approach will be to evaluate time and its influence on soil formation. This is referred to as a chrono sequence where we look at a soil property again organic carbon as a function of increasing soil age. In this particular example adapted from merits in 1991 we have depth on the y-axis and organic carbon on the x-axis. We see five platelets that show us different age soils and the amount of carbon stored within each. What you'll note in terms of the general pattern is that the carbon content increases with increasing age going from 3,900 years old to 240,000 year old soils. Again carbon content increasing with increasing age in soil. Again this is an example of how time conditions organic carbon content similar to the fashion in which we evaluated climate, biota, and geological substrate. The final example that I'll show you of any state factor approach is to evaluate the influence of topographic variations on soil organic carbon content. These data adapted again from Aguilar in 1984 demonstrate variations in carbon storage within grassland systems as a function of differences in topography. In this particular example we see the summit which is the upland soils to the foot slope which is the lowland soils. Large variations in the total carbon stored. We see other landscape elements the shoulder and back slope are also increasing in carbon relative to the summit. In this particular case we see the same relationship that we see in other soils with organic carbon content. Organic carbon content highest in the near surface environment decreasing with increasing depth in the soil. What's interesting to note is that we have a gradual increase in the carbon content as a function of topographic variation going from the summit landscape position increasing slowly to the shoulder, back slope, and finally the highest amounts of carbon stored in the foot slope position. Now the topographic factor is important because it modifies other soil forming factors. In other words when we look at topographic variations we have an understanding that there are key processes that occur within the landscape that modify sediment movement, moisture movement, and in effect change the climatic conditions at each point along the hill slope. So what I'd like to do is to delve a little bit further into the topographic variations that we see along different gradients. Now using a model of the state factor approach we can evaluate topography by looking at differences in elements of landscapes. The model presented by Rui and Walker in 1968 demonstrates that we have different elements of landscape units that essentially are delineated based on discordance and slope. In this particular example we see the summit, shoulder, back slope, foot slope, and toe slope landscape elements. Each of these will be discussed in detail. The components of the hill slope are evaluated based on discordance and slope but also on the configuration of the slope. In other words the summit landscape position generally possesses linear slopes, has vertical water movement, uniform soil material, and is generally well-drained relative to other components within the hill slope. The shoulder is the more steeping convex component of the landscape where we have maximum runoff, soil, and subsurface water movement are very evident. The back slope are the more linear landscape positions within this hill slope and they have both surface and subsurface transport of water and some sediment movement as well. The foot slope is considered to be the more concave component of the landscape and it generally receives additions of moisture and sediment from upland positions. And finally the toe slope is the concave to linear portion of the landscape that is characteristic of depositional landscape elements in any region with accumulations of both organic and inorganic materials. Now the next schematic shows how topography modifies climatic conditions. In this particular example we see a hill slope cross section that looks at the summit, shoulder, back slope, foot slope, and toe slope landscape elements. Essentially this example adapted from Birkeland in 1991 shows us how the hydrologic regime at each of these landscape elements is different as a function of topography modifying precipitation. In other words each of the landscape elements receives the same amount of precipitation but topographic variations that induce runoff and runon conditions generally modify the effective precipitation that each of these soils will see. This is an example of how topography modifies precipitation. We understand that water movement on landscapes is governed by many fundamental controls. The water movement on landscapes integrates soils in different parts of the landscape through process and through property. The major variables that govern water flow on landscapes deal with extrinsic and intrinsic properties of the system. The extrinsic properties deal with things like rainfall duration and intensity and the intrinsic properties deal with things like soil texture, vegetation type, slope form and angle. What this tells us is how much topography and to what extent topography modifies other soil properties. So to summarize the state factors what we understand is that the properties of the total system or its component parts, the soil for that matter, are dependent on related to or conditioned by the state factors. In this particular case we're going to take a closer look at how topography conditions soil properties across different environmental gradients. The beauty of the state factor approach is that it provides a conceptual framework that allows us to evaluate natural and agricultural systems and the changes in conditions of soil formation and how these influence soil properties. Next what I'd like to talk about are soil forming processes. Soil forming processes can be lumped in the four categories. The first category are considered to be additions to the soil. The second category are considered to be removals from the soil. The third category of soil forming processes are translocations within the soils. And the final category of soil forming processes deal with transformations. So again we have four general categories in which we lump soil forming processes. Those processes which are additions, those processes which are removals, those processes which result in translocations and those processes which result in transformations within the soil system. So let's take a closer look at additions to the soil system. Additions to the soil system encompass both organic and inorganic materials. Organic additions to the soils are primarily the result of the death and decomposition of plant and animal remains. These are adding mass to the soil volume. Inorganic materials can be deposited both in wet and dry deposition and as a result of depositional processes within a hill slope. Removals from the soil are both in the form of solids, liquids and gases. Again solids would be both organic and inorganic materials and removals primarily consist of erosional processes. Liquids can be removed by leaching the soil through evaporation and transpiration processes and gases generally leave by diffusion. In other words in most soils concentrations of gases are higher than atmospheric conditions. CO2 for example, where the concentration is anywhere from 10 times to 100 times more than in the atmosphere. This results in the diffusion of CO2 out of the soil, again a loss of gaseous material from the soil. Translocations within the soil result in differences within a soil profile. Again this could be both with solid materials which encompass both the organic and inorganic compounds within the soil and also liquids in which dissolved salts are transported from one part of the soil profile and deposited in the other. Again translocations removing materials from one part of the soil depositing them in another. Organic and inorganic as well as dissolved constituents. The final general category of soil forming processes is encompasses transformations within the soil. These are both again organic and inorganic in nature. For example the transformation of organic compounds for example nitrogen which is 98 percent of which is in an organic form is transformed to the inorganic form through the process of nitrification. Again a transformation of organic to inorganic material mediated by microbial activity. Other types of transformations that occur in soil are weathering processes in other words taking a primary mineral like a feldspar weathering that transforming that to a kaolinitic mineral or a smectitic mineral depending on the environmental conditions. We also see transformations in the soil that are related to hydrological conditions and these are specifically mitigated by oxidation and reduction reactions. What I'd like to do now is to present the key soil and ecosystem properties that vary as a function of topographic position. Plant production, soil organic matter decomposition, erosion, deposition and leaching. These are all key soil forming processes that result in differentiation of soils across topographic gradients. In the first example on the platelet to the left these are data adapted from Schimel in 1985. We're looking at plant production as a function of distance from the summit. In other words on the y-axis plant production is in kilograms per hectare. On the x-axis we're looking at distance from the summit. We note that both above and below ground biomass increase with increasing distance from the summit. In other words when we go from the uplands to the lowlands we see generally an increase in the amount of above ground biomass that's produced as well as below ground biomass. Along with this relationship of a above ground and a below ground biomass what we note is an increase in the platelet to the right in the nitrogen mineralization along the same hill slope. In other words the uplands have lower mineralizable nitrogen than the lowlands. So key processes that are vital to ecosystems are varying across this topographic gradient. The following schematic shows the differences in leaching erosion and deposition across a hill slope. What you'll note from this example is that the soils in the uplands are generally immature, possess lower amounts of clay, have less leaching and less redoxomorphic features. As we move down the hill slope to the lower slope in the mid slope position what we note is that these soils have much more pedagogical development, higher amounts of clay accumulation, the possess greater amounts of redoxomorphic features, greater amounts of clay, suggesting that the weathering gradient is increasing from top to bottom along this hill slope. These are data adapted from Gerard in 1981. What we see is that the weathering process encompasses all of these leaching deposition and erosional processes. So the hill slope expresses differences in soil formation as a function of topographic position. Now what I'd like to do is focus a bit on key soil properties and how these vary as a function of topography. We have physical, chemical and hydrological properties that are basically conditioned by soil forming factors. What we're going to do is evaluate how topography conditions physical, chemical and hydrological properties within soils. Soil physical properties that are important to the management and sustenance of ecosystems are as follows. Soil texture provides a general information regarding the amounts of the sand, soil and clay size particles. We know that soil texture is conditioned by things like parent material and weathering. It is also conditioned by topography due to the result of erosional and depositional processes. A second property that's important to ecosystems is the soil bulk density which is just a measurement of the dry mass of the soil per unit volume. It integrates other key soil properties such as organic carbon, texture, organic matter, nitrogen and roots. All of these are important to determining what the bulk density of a soil is. Again, these types of properties are conditioned by these state factors. Depth to bedrock influences the depth to which roots can penetrate the soil. Again, topographic variations, parent material type have a profound influence on the depth to bedrock. Other soil physical properties that are important relate to the aggregate stability within the system which generally affects the soil by allowing water and air to move through the system freely. Soil color is also an important property of the soil that's related directly to topographic variations. We evaluate soil color looking at the U value in chroma utilizing one cell color charts and we know that the soil color reflects differences in organic matter content, salt content, oxidizing and reducing conditions. Again, each of these properties is intrinsically tied to topographic variations within systems. Soil chemical properties also suggest that topography has an enormous influence on soil formation and soil properties within a landscape element. Organic matter content as we suggested earlier is related to each of the conditioning variables of soil formation and tied intimately to topographic variations within a hill slope. We understand that organic carbon accumulation is the result of opposing processes, primary production and decomposition, the balance of which varies as a function of topographic variations as we pointed out in that Schimmel example earlier. Soil pH is another soil property that varies as a function of topographic variations. It gives us an indication of the acidity or alkalinity of the soil. It also gives us an assessment of the nutrient status since it's considered to be a master variable in terms of evaluating plant growth. Other chemical and properties that are important are the soil salinity which gives us an indication of the amount of salts that have accumulated in the soil. It links to processes of leaching, evaporation and transport and is related intimately with hill slope position. Cation exchange capacity gives us some indication of the nutrient retention capacity of the soil and is intimately related to weathering processes which again vary as a function of topographic variation. Not only is it weathering variations but also the transformations are primary to secondary minerals. Finally soil hydrological properties vary considerably as a function of topographic variations. Things like plant available water content which is just an index of the amount of water that's available to plant growth vary systematically along hill slopes. Infiltration rates again vary as a function of hill slope but other soil properties such as texture, coarse fragments and vegetative cover. Other hydrological properties that are important in evaluating hill slopes are permeability which is just the ability of the soil to transmit water and then water table depth which influences the redox relationships within a soil profile. So what we understand is that landscapes and landscape components display systematic differences in soil properties as a function of soil forming processes and we understand that the soil forming processes are modified by topographic variations. In other words topographic variations modify soil forming factors and result in unique properties within systems. The first example is to evaluate the position in the landscape and how this influences three key properties of the soil. In this particular example taken from Birkeland in 1999 we note soil depth on the y-axis and slope gradient on the x-axis. What we note is that the steeper the slope the less soil development. These data suggest that B horizon thickness is maximized where we have the lowest gradient of slope. We see similar relationships with the accumulation of bases in the soil noting that the depth to 80 percent base saturation is much deeper in the topographic position that has no runoff versus the landscape position that has maximal runoff that would be the back slope in this example. We also note that the organic carbon distribution in the soil is very different as a function of topographic variation. Increasing slopes generally result in lower water infiltration, more runoff and less carbon accumulating deeper in the profile. In this particular example the summit displays the greatest depth to one percent organic carbon among the three landscape elements because it possesses the lowest gradient of slope. Another example of a soil property that varies as a function of topography would be available water holding capacity. And what we note is a variation in this particular example between the summit and the foot slope. Along the x-axis we see the mean annual precipitation or the monthly precipitation as produced by Hannah in 1982. We note that in every case the foot slope possesses greater amounts of available soil water relative to the summit regardless of what the meteoric water conditions are. The next example of soil properties that vary systematically as a function of topography would be something like pH which again just gives us an index of the acidity or the alkalinity of the system. In this particular example we have a comparison of calcareous soils which are soils that possess calcium carbonate versus acidic soils which are generally soils that have low pH's and are depleted in base cations. What we note is in the calcareous soil that with increased gradient the pH of the system rises suggesting that we get less water infiltration, less weathering within each of these systems. In the acidic environment increased gradient results in a decrease in pH where we have less weathering the natural acidity of the system is not augmented by leaching or weathering processes. So in two different systems a calcareous system or an alkaline system versus an acidic system we see that the effect of gradient or slope gradient on the property is very very different. The next example from the literature suggests from Birkeland in 1999 suggests that water flow in the system determines the accumulations of basic cations and anions within the soil. In this particular example what we're noting is a soil solution concentration in milligrams per liter on the y-axis and then each of the anions and cations are grouped on the x-axis and what we note is that in each and every case the lower landscape positions maintain higher amounts of anions and monovalent and divalent cations suggesting preferential flow and water accumulation in these systems. Again you'll note that the back slope is actually lower than the summit or foot slope and the back slope is the more sloping landscape element higher gradients with regard to slope and thus more runoff. So in this particular schematic we see the foot slope accumulates most of the anions and cations the summit is actually intermediate and the back slope with a more sloping topographic position has the lowest amounts of anions and cations. In summary the degree to which soils and soil properties vary within landscapes is predictable and it's based on an understanding of the fundamental factors and processes of soil formation. Again the relationship between factors process and property and now what I would like to do is I'd like to take it four examples from the literature that look at soil formation and how conditioning variables affect topographic influences on soils. The first example is from a hot wet climatic condition in the southeast in the United States with a mean annual temperature of 66 degrees Fahrenheit and a mean annual precipitation of 45 inches. In this particular example what we note is variations in soil formation and soil properties as a function of topographic variations. In this particular example the upland soils which are plinthic candy udults in both cases, this is denoted by the blue and the gray outline on this particular figure, show that the soils are well developed and well drained. As we follow along the hill slope what we note is that the aqueous happily udults and the tippic candy udults are further downslope and receive moisture from the upland positions. Thus the aqueous subgroup suggests that these soils are wetter than the soils in the upland position. You'll note the depositional nature of this environment by the presence of the tippic quartzy salmons down in the lower landscape position. Again differentiation in soils and soil properties as a function of topographic variations. The upland soils possess soils that are well developed, well drained. The intermediate soils that are receiving moisture from the uplands are generally less well drained, in fact poorly drained with the presence of an aqueous subgroup and the lowest part of the landscape position we see depositional soils. Now if we look at topographic relationships under different soil forming conditions in this particular case a cold wet environment where mean annual temperature is about 50 degrees Fahrenheit, mean annual precipitation is about 120 inches. What we note are systematic differences in the soil properties as denoted in this cross-sectional figure. The bell grade, gloster and Paxton soils are all upland soils well drained, well developed. What we notice the bell grade is actually intermediate between the uplands and the lowlands and has an aqueous subgroup suggesting that this particular soil is affected by water table or sublateral flow from the upland positions. The sun, cook, awanda and winds of soils are all lowland soils. They possess weakly developed soil profiles suggesting that deposition of material from the upland positions. Again weakly developed soils in the depositional landscape positions well developed soils in the upland more stable positions topography imparting its influence on soil properties across a very large area in this particular case again a cold wet environment. The next example from the literature looks at the depositional nature of landscapes looking at a cold dry environment and this is an example from the Bitterroot Valley in Montana. Mean annual temperature is 46 degrees Fahrenheit, mean annual precipitation is 15 inches. What we note is that there are fundamental differences in the soil properties as a function of landscape position. You'll note that the calcic haplocryols, the xerolic nature arches and the calcic haplocryols all occur in the lower landscape positions. Each of these soils accumulates key soil components for example the xerolic nature arches accumulate large amounts of sodium whereas the calcic subgroups and the haplocryols accumulate calcium carbonate. These landscape elements receive material from the upland positions which are the tippic cryocreps and the tippic haplocryols as well as the mountain lands. In each and every case the low lying positions in this particular region are more well developed because this region is limited by precipitation. In other words topography imparts its influence by looking at differences in soil age as a function of topographic variation not necessarily the distribution of water. We can have dry input of calcium carbonate, sodium and other salts which again would impart differences in soil properties. The final example that I'm going to show you is from a hot dry environment in New Mexico with mean annual temperature of 62 degrees Fahrenheit and the mean annual precipitation 12 inches. In this particular case what we note is large variations in soil properties as a function of topographic variations. The Simona, Potter and Bipus soils are all located in what we would consider to be upland positions. In each and every case these soils are the most well developed. In other words they're unstable uplands and possess horizons that are solidified. For example the Simona is a tippic petrocalcid which suggests that the soil has been stable for many thousands of years. The Potter and Bipus soils are the same. We note that the Largo and Pajardo soils or the tippic capital canvads are located in the lower landscape position. In each case these soils are weakly developed and possess no diagnostic features that suggest that topography modifies soil formation. Again in hot dry environments it's not necessarily the modification of water across these landscapes what we're looking at is different soil ages as a function of topographic position. The older landscapes possess soils that are well developed, the younger landscape possess soils that are weakly developed. In summary the need to understand the distribution of soil properties and soil behavior is indeed imperative to the management of both natural and agricultural systems. Landscape units display systematic variations in soil properties as a function of relief modifying other soil forming processes for any individual reason. So now you're viewing the soil as a pedologist and as a pedologist what we understand is that we try to relate soil forming factors to soil forming processes to soil forming to soil properties. Again factors condition processes which result in unique properties. What I hope to cover today was to show you that topographic variations have a profound influence on soil properties and the influence varies as a function of the other conditioning variables. For example climatic variables, geological variables and biological variables. Thank you.


They traded their pick to the Eagles. Oh my gosh, the Eagles. You know what's happening You already know what's happening. Yes, we go ahead and say that the Eagles are officially on the clock Should I say it should you say it I think chat should say it chat What do you think is gonna happen with the Philadelphia Eagles because we know what's gonna be happening with the Philadelphia Eagles Yeah, now they're often to player off the board here at the last great wide receiver in that Tier yeah, yeah, they get a husband potentially if this is what they do but Devontae Smith, I mean They they couldn't wait any longer I don't know if you know who's next on the clock It would have been the Giants the Giants could have took in Devontae Smith Yeah, especially, you know, he was at a Knicks game or was it maybe it's a Nets game either one in New York You know something like that. So, you know Philly had to move up. They they made a big move and you look at Philly last year I couldn't even name the receivers that were playing Yeah, you had people like our Sega Whiteside playing Jalen Rager Could work out. Yeah, I don't know. You had Greg Ward the former quarterback I did not have that bad of a of a stretch but They also need to add to that receiving room and you know, I think they go Devontae here Oh, absolutely. Like you're gonna look at ESPN right now showing footage of Devontae Smith Waiting in the war room just because it's It's pretty evident at this point that they're gonna be taking Devontae Smith. Yeah.  It's okay. Yeah, and you see officially Let's go ahead and throw that up that Eagles get the 10th overall pick surprise as Expected we've got Devontae Smith The Heisman trophy winner being taken By the Philadelphia Eagles after they traded up To make that aggressive move by Howie Roseman and that Eagles front office to get Devontae Smith Mikey You like this pick a lot of people have been criticizing him because of his size and saying that he's a little bit under Underweight, but people are saying that unless this isn't about bodybuilding. This is about being a football player What are your thoughts on Devontae Smith? I love it. He's as classy as it gets It was very well respected first wide receiver when the highs been you know sent to What Charles Woodson and when he played both sides of the ball like he's just the lead you know he's up there with waddle and Jamar Chase like we said on that like top tier receiving group And people concerned about his weight I mean, I think that's just a bunch of BS because if he can play in the SEC he can play in the NFL if he can survive the SEC which Honestly, I don't even know if Devontae missed a game at Alabama didn't seem like it But you know, he's kind of a guy that can do it all you can run vert. He's top tier Route runner can run slants vert, you know move them inside outside. I love it and Obviously, it's much needed for the Eagles because All their receivers were hurt last year or just didn't perform So Yeah, it's and you saw the ESPN footage if you guys are watching their coverage You saw that his comparison was Calvin Ridley, which is a pretty good comparison another Alabama wide receiver and Devontae Smith You know, like I said, it's you know route running abilities his speed is athleticism. It just speaks for itself


We felt that this was an opportunity to come into the epicenter of creativity and see how we can raise our creative game. Thank you Mark for joining us. So how has your can been so far? So far so good. We like to view ourselves as the hardest working company in the festival. We come here with a contingent of top talent so they can learn, get inspired, and help us raise the creative bar to the next level. If I'm not mistaken, you were one of the first kind of marketable organizations to actually come to Canada. That's right. Significant numbers. That's right. That's right. We was almost, I guess, close to 20 years ago when we came here for the first time because we felt that this was an opportunity to come into the epicenter of creativity and see how we can raise our creative game. The focus is on creativity. But the thing that we, as much as we are celebrating the craft, there is also the impact that it has. And so, you know, this is creativity with a goal in mind. And I'd love for you to talk a little bit about kind of the role that creativity plays in your organization. What are you driving to achieve? The products that we offer to the world's consumers are everyday household and personal care, cleaning health and hygiene products that almost everybody uses. So in a large way, all of our consumers in the world are potential consumers. And so what we do creativity as is a way to reach all those potential consumers, identify what each of their unique needs are, and then use creativity to be able to communicate what the product is, what it does, why it's better. How, tap into an insight that that consumer will recognize, say, you're really speaking to me, and then be so effective that it makes the market bigger. It's creativity that grows markets. So when markets are bigger, that means what you're doing is you're attracting more people to the market, you're offering them a better performing product. Hopefully they will use more of it, but in a responsible way. And when you grow markets, all boats rise. So that's, creativity is core to our entire superior strategy, a superiority strategy, and delivering a superior consumer experience. So creativity that grows markets, that, I like that a lot. You actually use the word insight, actually, in the lead up to that, and I think it's true that for creativity that the start point is an insight and a strong insight. One of the challenges in a lot of your brands are global brands. And so trying to find an insight that resonates globally without it being the lowest common denominator is kind of a huge challenge. How do you go about finding insight? Every market in which we compete on every single category, we are out connecting with consumers in their homes and stores, websites, e-commerce, wherever it may be. We even have a lot of connected homes that have measurement sensors. So we understand the actual consumption behavior, and then we have vast amounts of research data. But it's very, very focused on the local consumer, a good example of this. In the dishwashing, automatic dishwasher, do you have a dishwasher? I do. Okay, good. All right. So how often do you use it? Every day. Every day. It's my job in our house. You're perfect. So that's great, but not everybody does that. So 70% of the households in the United States have a dishwasher. They're used only about two to three times a week. 20% of people don't use it at all. So what we tried to do is say, okay, why is that? Doug Deeb, they felt that dishwashers waste water. So we created a new idea called do it every night. Cascade, do it every night. When the dishwasher every night, you're already on this. But that idea then helped bust the myths that a dishwasher uses more water than hand washing. Turns out, a dishwasher uses four gallons of water per cycle. Washing by hand, four gallons of water every two minutes. So they took that unique insight and translated it. They tried that insight over in the UK with Ferry Dishwasher, which is the auto dishwasher there. Very similar. 80% of households have it, two to three uses a week. The issue there was energy. Energy was a bigger issue because energy prices were up. People are very, very cognizant about energy and emissions. So and what they focused on was that on water, they focused on energy through turning to the short cycle. So turning to the one hour short cycle versus the three to four hours. And what they found is that product works better and it also helps you reduce 33% of your energy bill per use. So that became more appealing. Great example of different markets, similar idea, you want clean dishes. You also want to make sure that you're doing it in a way that's potentially better for the environment. But they found it in a different way through each country based on the insights. It's what I found fascinating about that insight, particularly as you talked about consumers in the UK and energy prices, that demonstrated a sense of empathy, like an understanding of actually this matters to our consumers, I mean to put myself in their shoes. How do you kind of ensure that all of your marketing is as empathetic? We spend, we really just love connecting with consumers. Our job is to make sure that we make their lives better a little bit every day. And it is one of the most noble jobs in the world when you think about it because these are products you use every single day. And so you'd be amazed at the passion commitment that the people at P&G have for the consumers that we're serving. So then when we understand and then extract these insights, we're like, wow, okay, this is great. We're really going to make people's lives better if we do this. One thing, I'll give you an example on Pantene. Pantene's a brand that in Brazil, what they found is in Brazil, they weren't appealing to a large part of the population. The brand was not doing very well. Part of it is they looked at the makeup market and they said, makeup is 55% black and brown. We're not even representing the black and brown community in there and we're not representing their hair. Curly hair in Brazil is a huge part. So what they did is they did a whole campaign on really celebrating curly hair. All sorts of different curly hair. And it's a beautiful campaign and the business has gone up like that. In Europe, they've looked across and said, okay, we're going to celebrate Caucasian hair, Asian hair, black hair, Hispanic hair. Gray hair, women in menopause, we're going to focus on Lucy Edwards, who is a influencer who's vision impaired, who has the feeling of hair. And then the LGBTQ plus community focus on the fact that hair is a unique and meaningful expression of identity. So we have this campaign called Hair Has No Gender. So deep empathy, same thing. And what it has done for that brand is that it has appealed to all consumers, each individual consumer in a unique way. It has built the brand and it has built the market. And that's what creativity is all about. And that's what human insight, empathy, that then allows you to serve all on each. So it's insight, inclusiveness, as well as impact. All three of those things are what you need to do to reset the bar, to drive creativity that grows markets. So that hair example is a great example of talking to all people, but there is a unique relevance to each. Exactly. There is some work that, I think it's Old Spice, the writer's room, I'd love you to talk a little bit more about that. I feel like... Old Spice is such a great example. A brand that was growing and doing well, part of the problem though is that when we looked at... When the team looked at the individual, each of the individual groups, they found, we're not growing among black men. Why is that? We have representation in our advertising, so why is that happening? When they dug deep and went deep into the insights, they found that, first of all, black men really care about their skin, and so it's deeply care about their skin, do a lot to take care of their skin. So it was this truer insight about them, and that is true for everyone. And then what they found is that there's this tension between men and women in some cases on using your personal care products or any product, so that could create some creative tension. And then they looked at the humor, and they said, we need to make this humor more sophisticated and more real, so black men and women look at it and say, okay, they understand that. So that's where they got Gabrielle Dennis, Dionne Cole, Millison Shelton, who's a black director, and created the Men Have Skin Too campaign. And that was a breakthrough. And then they've worked with Kevin Hart and Kevin Hart on Heartbeat Media, LOL Studios, to create these funny sketches. And the writer's room was a brilliant one, because it was one of their writers whose girlfriend had been using his Fiji scent product, and he was angry about that. So they did a role play, and it was just, you look at this and use it. It's so funny, but the product is woven into this perfectly. So you remember Old Spice, and it's been very, very successful. We often talk about representation as sort of on a hierarchy, because as you talked about, there was black men in the advertising of Old Spice, and I remember it. But that's just the base level. With the writer's room, you kind of went into this understanding of the culture that's nuanced as a consumer. That's it. You get it. You start with representation, good start, then you go to relevance, which is insights and nuances. Then you go, when you create then that work, which is very nuanced and it's funny, it's funny to everyone, very, very true to the black community. And then put it on Heartbeat Studios, that's relevant advertising on resonant media. You have the recipe for really good growth. So there is one campaign that I'd love to just touch on, which is one of the great examples, but this one was around period protection, and I've worked in the category. So I feel partly responsible for some of the myths and misinformation that you were pushing up against. I'd love you to just talk a little bit about that work, because I found it really culturally relevant. Well, period protection is a big market, big opportunity, but it is fraught with misinformation and myths, and it's different in every country. So if you go back again to our earlier discussion about insights, go to India, for example. In India, one out of four girls miss school, one out of five girls miss school, 23 million girls a year miss school during their period. And a lot of that is due to lack of information, lack of education. So the creative idea that the team put together was, let's educate, not just the girls, let's educate their moms, because what they learned is that if the moms aren't educated, then the girls won't be educated and they won't go to school. So they created this program called this film and program called The Missing Chapter. It was a missing chapter that wasn't in the education system, that wasn't in the books that talked about menstrual and period protection and menstrual education. Beautiful film, really a very, very, very, very powerful, won a Grand Prix last year. And importantly, it's up for a creative effectiveness award this year, and we love that, because it grew the market, it changed the nature of the education in the system, and they even changed the education system, they put the chapter in. So that's a very impactful piece of work. The other one is Always, Always is a brand, there's a product called FlexFoam that is the peer protection brand made for anybody and everybody, because the insight, particularly in Latin America and the U.S., is that the wrong size pad is often used, based on body shape, size, so you need to help people understand how to be able to use the right size pad for the best protection. And one of the most amazing examples of growth in terms of education was Tempax, because tampons are a high performing product and highly misunderstood. So we worked with Amy Schumer to do some very funny education. I would ask you to go take a look at it, particularly look at one which we showed, which is the gynecologist visit, where you just go through myth after myth after myth, and it helps people overcome the myths in a humorous way, because the team says, if we can laugh about it, we can learn about it. And it's so important, because these are tough subjects, you know it, they're tough subjects in taboo and many places, so you have to find very creative ways to be able to overcome them. And it's been great for this business. The team is amazing. It's funny, I used to, many years ago, I worked on the launch of UbiCotex, which is when I was, yes. Oh yes, oh my, you were right. And we went right at the myth. Oh, and you did a great job. I tell you, you did a great job on that. That was really good. And it was, because I was literally the father of a daughter who was literally about to start a business. I was really personally invested, but the funny thing is, I learned so much about millennial girls, or Gen Z girls and periods, and then my wife calls me, she's like, Saffy, you started a period. I was like, I am so ready. Am I ready? Literally, I left the office, I ran home, and I got back, and I was like, Saffy, stand, and she went, I don't want to talk about it, I'm just slammed the door, and that seemed to be it. Exactly. All that knowledge. I couldn't use it. That's why if you look at the Amy Schumer kind of college, it's just great. She just goes, she just knocks every one of them down in a hilarious way. So what you're articulating, and I like it that you actually didn't use the word, but it was purposeful. Like, there was purpose behind this, but at the same time, it grew the business. Yeah. And it's an important point, because what I think brands, what they can do is they can make a difference by focusing on what they do best, and what they do best is a superior offering, a superior product, how it's better, how it works, education makes it better. So what it does is it improves lives by just delighting the consumer on an everyday product, and it grows the market. That's what we do. And it's a heavy lift for household care and personal care product. Very heavy lift, but one of the biggest creative challenges is to make this kind of work interesting and useful and grow the business. But that is what we do. That's what we try to do at least. One last question. This is about looking forward, but I'm not interested in technology because there's a lot of that conversation. Going back to creativity, and I'm curious about kind of if we think ahead to can in 10 years' time, what would creativity look like? What will our canvases be? I think our canvases will continue to grow like they have in the last 10 years. They will continue to expand to different ways that we can engage with people, and who knows, based on the fact that technology exponentially grows every 18 months, it's going to be some amazing ways in which we can engage, probably going to be far more experiential, far more useful, far more precise, far more individual. But the components of what makes successful creativity will be the same in my view and in our view. Because they've been the same for hundreds of years, or at least 187 years, which we've been around for. Because you need to understand that consumer insight. What's the job that we need to do that a product needs to do? What's the problem that needs to get solved? What is the product? How does it work? How does it make it better? Why is it better? And then what's the benefit that you receive? I think those components will stay the same. You just need to apply them to the different parts of the creative canvas. Yeah. That makes a lot of sense. The approach is consistent, the execution will evolve. Yes. Perfect. Thank you very much. You're welcome. Thank you. It was a pleasure.


Hey, everyone. My name is Joe Elliott, and we're going to talk about getting started with Yeager today. This presentation is mainly aimed at people who are, you know, getting started maybe building their first production cluster. Maybe you've already set up a proof of concept and you're wondering kind of what it takes to get this into production. Or maybe you're just interested in tracing in general, see if it's something that's worth doing for you all, and you want to know what Yeager looks like and kind of how Yeager is built. So who am I? Let's start with that real quick. I'm a Yeager maintainer. I work at Grafana Labs primarily on our tracing infrastructure and internal projects.  Yeager is the most popular distributed tracing backend open source. It is a CNCF graduated project, and originally it was created at Uber, an open source by Uber. I think it began in about 2015. And before we get into the actual architecture, I want to talk a little bit about what a trace is, because, you know, kind of what a trace is and how traces are generated kind of inform how the actual backend works. So understanding what trace is helps us understand why the backend, why the Yeager ingestion pipeline is the way it is. So this is a trace from Loki, and this particular trace represents a single request. So this is one request to get 35 milliseconds to get through the Loki, or to be answered by Loki. I mean it's passed through a number of different applications and services. So you can see there's like these green bars, Loki Gateway at the top, and then query front end orange, and then Loki queers these blue ones all over the place. These spans kind of represent maybe like a single functional or logical unit inside of our application. And the application, each process, and there's lots of these of course, are going to be generating spans and have all this data like when they started and when they ended, some other metadata of course. They're going to create these spans, they're going to offload those into the Yeager kind of ingestion pipeline. So all of these different applications are going to be creating spans, pushing them into Yeager. Yeager has to then absorb all these, bring them in, put them somewhere, and prepare them for querying. And so we'll talk a little bit about how that looks and why it's built the way it is. This is the architecture. So given that in mind, we have all these applications, right? And all these applications are going to then be pushing all their spans into the agent from the client into the agent. The client itself, to start there, it's on this side, this side. The client itself is a part of your applications like a library or a framework that you bring into your application to create these spans and offload them to Yeager. There's lots of different applications or frameworks and language supported like popular ones like Go and Java, Node, Ruby. So all these different popular enterprise languages have support for Yeager. Or Yeager has support for them perhaps. And you create these spans in your applications using client which is then offloaded to the agent. Where the agent is positioned is important. We'll talk about that a little bit in a second. There's a lot of options about where you put the agent in relationship to your application. The agent then moves them over to the collector piece. The collector then has to make a choice about, or sorry, doesn't make a choice. You make a choice about how to set up your pipeline. You can either at this point point it directly at a backend database or you can use this Kafka Ingestor optional kind of piece. We'll talk about some of the choice there or why you would choose to use this. So agent or sorry, client in my application to the agent layer, to the collector, optionally Kafka and then an Ingestor and then our backend database. And then the Yeager query piece, which we won't really talk about much. The Yeager query piece just speaks directly to your backend database. So how am I going to deploy this? I'd say there's three probably popular options here. Helm. A lot of people like Helm. It's great application. It's a great way to deploy things to Kubernetes. The operator, mainly I believe maintained by JP is an excellent choice for deploying Yeager. And then there's the custom option as well, just however you all want to do it. So maybe you just have custom YAML, maybe they're just sitting and get somewhere. We use JSON.actually at Grafana to deploy Yeager. I'll say that Yeager itself is not very difficult to operate. Your operational complexity is going to come from your backend. The database you choose to put your spans in. So Yeager itself is mainly stateless. It has cues, it keeps things in memory, but it's easy to operate. It's easy to monitor and to manage. It's not very difficult. It's kind of the backend that's going to give you trouble. Or maybe not give you trouble, but is the source of complexity of operating Yeager. The operator is a cool choice because it supports some different agent modes like sidecar injection, or as daemon set sitting on your hosts, and we'll talk about why you would choose one of the other in a second. And then of course Helm, Helm's a great option. We used Helm at my previous position quite a bit, and Helm's a great way to deploy applications as well. So some of the very first things you're going to be picking when you start building your first production Yeager cluster is the backend database to use, Elasticsearch or Cassandra. These are the production supported Yeager backends. There's others, but these are the two that I would recommend. Elasticsearch is the recommended choice by the Yeager team. It has a little bit better flexibility. It has a little bit better search flexibility and capabilities than Cassandra does. And the amount of load or kind of the size of the cluster will be roughly the same between Elasticsearch and Cassandra. Cassandra is not bad. In fact, we use Scylla, which is kind of a Cassandra alternative at Grafana, and it works fine. There's like maybe slightly less flexibility in searching, but we use it and we have no problems. So if you have a ton of operational experience around Cassandra and you don't want to kind of take the risk on of building or understanding a new backend, then Cassandra is 100% worth, or 100% a good option we use at Grafana, and I'd recommend it if you have just far more experience operating it than Elasticsearch. The other option you have to pick is Kafka or not. So we talked about this optional Kafka piece. You have client, agent, collector, and then this Kafka ingester, optional part. The Kafka piece is useful in some ways. You kind of have this durable queue for a lot of people. In fact, Kafka is very easy to run, especially maybe compared to Elasticsearch or Cassandra, at least for us it is. And it provides some more flexibility kind of in your pipeline. If you're backend stutters for a little bit, Kafka very nicely and easily queues these pieces up, and then once your backend's back online, it can continue pushing spans in there. There's also some kind of neat integrations with Kafka, with Kafka streaming to do analytics, and to do some other kind of like data processing on the spans they come through.  It gives you the flexibility maybe of writing your own kind of like applications that watch the Kafka stream, maybe generate some metrics, or provide some kind of information about your infrastructure that is difficult to find otherwise. And if you do make something cool like that, please share it. Please share it with the community. Yeager's open source. We love contributions and involvement, and if you build something very neat, we'd love to hear and see it. A final choice here is kind of the positioning of the agent, which we've kind of alluded to a few times previously in this discussion. The agent, the common wisdom here is to put the agent as close as you can to the application. So the operator does this kind of nicely for you. It'll do this sidecar injection, where you have your application, and then as a sidecar, you'll be running the agent. So it's sitting there in the exact same network name space, and every application's going to have its own agent right side by side. Excuse me. And this would be the absolute fastest way to offload spans from your application. The kind of game that's being played here is your application's generating spans extremely quickly. You're filling up a queue in the client, a configurable queue in the client. There's workers that are draining that queue as fast as possible by sending spans over UDP to the agent. So the closer your agent is to your client, the fewer drop spans you're going to get. So a sidecar for the most high volume applications, a sidecar is as good as you can get putting your application a single agent as close as possible to your application to get those spans off as quick as possible to have as few drop spans as possible. Other popular options are to run it as maybe a daemon set, or if you're not in Kubernetes, just on every host, and then have all of the different applications on that host speak to your local agent.  We do have drop spans at Grafana, and I sometimes wonder if we should move to sidecar or maybe this daemon set approach. We haven't yet, and we do have some drop spans, and sometimes I think it might be a good choice for us. So I will say, if you want to run it as a service, you want to run this simple option where you just have a collection of agents that all of the different applications in your cluster point at, it works, but you're going to have a few more drop spans than normal. And then for your highest volume things, use a sidecar or maybe some of these other approaches to get your agent very close. Sampling. So sampling is a very important choice, understanding sampling. Sampling allows you to only record a certain amount of your total traces into your backend. Most of us cannot afford to sample, to record 100% of every request in our infrastructure or backend. They can kind of quickly get out of control. Development teams are going to start adding spans. Hopefully your volume is going up. Somebody throws a new service in, which is going to add more spans, of course. All these different kind of changes always are growing. It's always making your span count grow, and you're going to find that it's very difficult to do 100% sampling. Or at least, maybe not difficult, but costly. Your backend Cassandra Elastor Search is going to be very large once you're hitting a large number of spans per second. 100,000 is an enormous number of spans per second. So our options for down sampling from 100% are probabilistic or rate limiting. Those are common options. Probabilistic is where you're going to say 10% of every trace initiated by the service I want to actually save. Rate limiting is going to say 5 requests per second, 5 traces per second initiated by the service I want to actually save in my backend. And so you're not sampling 100%, you're sampling this lower amount, and it allows your backend to kind of survive the storm of spans that are coming in. The next part I cannot emphasize enough. There are these different sampling options like probabilistic and rate limiting, which are fun to work with. I think for production instance shared by multiple teams, there is no substitute for remote sampling. I'm going to just tell you to set up remote sampling. Remote sampling allows you to centrally control all of the different services and their sampling rates. So you as the Yeager operator sitting here one day, and all of a sudden your spans per second go from 5,000 to 7,000, and you don't know why and your backend is struggling and you can't figure out what's going on, and you don't have control over these applications that are creating spans.  So it allows you to kind of maintain this document, and you can kind of see it over here. You can maintain this document that says for each service what percentage of span or what percentage of traces do we want to actually save from that service. You can even do it per operation. So maybe you have like end points that you don't care about. You don't ever want to sample those. You can set those to 0%. End points you want every single trace to be saved for. You can set those for 100%, and of course anything in between. Remote sampling gives you this extreme flexibility of sampling that you're going to need as an operator. Some development team somewhere is going to start slamming your backend with a ton of traces or a ton of spans or both, traces and spans. And unless you can control that as the operator, you're just going to get overwhelmed and you're going to have to go like scramble around, talk to these development teams and you're kind of at their mercy. Remote sampling gives you the control you need. Absolutely 100% recommend remote sampling. Monitoring. So monitoring Yeager is actually pretty straightforward. It has really good logging, standard out logging like everything else. JSON logging, if that's your thing. It also has Prometheus metrics. So really the open metrics format. So there's lots of different applications. Of course, Prometheus itself that will scrape those, store those and allow those for query. And the metrics are very descriptive. They're very easy to read. In fact, a personal thing I do when I start any application is I curl the metrics endpoint. I just start reading it because the metrics endpoint on a well-designed application will give you good information about the internal to that application. And Yeager absolutely falls into that category. So just reading the metrics is going to tell you a lot about what's going on inside. And finally, everything is a queue. So the client in your application has a queue, the agent has a queue, the collector has a queue, Kafka is a queue if you run that. The ingester is the only piece that doesn't really have a queue. And these queues can get filled up and start dropping spans. And that is the number one question your developer is going to come to you with. Where are my spans? Like, why is my trace broken? Where did all my spans go? It's going to happen over and over again. So understanding how to diagnose this ingestion pipeline, all of these different queues is critical for like having a healthy Yeager instance that your developers rely on and trust to store their traces and trust to go find their traces when they need them. There's a medium article that I recommend called Where Did All My Spans Go? And it walks you through every single piece and all the metrics to watch and tells you exactly how to kind of track down where your drop spans are. Also, there's a couple of other links there, the monitoring and troubleshooting links on the docs are also great for figuring this out. Finally, a couple of resource links. There's the docs. The docs are really well done. Please go read those. If you're interested in Yeager, please submit PRs to improve them if you have some problems or if there's something you want to clarify. The Gitter. The Gitter channel is haunted by myself as well as some of the other maintainers and is a great place to get answers to getting started questions, a great place to just kind of move past some initial hurdles to understand what's going on or how to get your basics going. Or also just to chat generally about Yeager, of course. And then the Medium Yeager Tracing Blog has a lot of great articles from all of the maintainers that talks about all kinds of different ways to use Yeager and new and clever ways to work with it and how to diagnose issues and absolutely a great place to go if you find yourself working with Yeager a lot. Thank you all. I hope everyone has a great Kubecon and I will see you when I see you.


Welcome back, we're winding down the Cube's coverage of Red Hat Summit 2022. We're here at the seaport in Boston. It's been two days of little different Red Hat Summit. We're used to, you know, eight, 9,000 people. It's a much smaller event this year. Fewer developers are actually, in terms of the mix, a lot more suits this year, which is kind of interesting to see, you know, that evolution and a big virtual audience. So, and I love the way the keynotes we've noticed are a lot tighter. They're pithy, on time. They're not keeping us in the hall for three hours. So, we appreciate that. Kind of catering to the virtual audience. Dave Vellante here with my co-host, Paul Gillan. As I say, things are winding down. There was an analyst event here today. That's ended, but luckily we have Jim Mercer here. He's a research director at IDC. He's going to share maybe some of the learnings from that event today and this event overall. We're going to talk about Dev SecOps. Kirsten Newcomer is director of security, product management, and hybrid platforms at Red Hat. Folks, welcome. Thank you for seeing me. Thank you, great to be here. Yeah, so it's, you know, security's everywhere, right?  We've done some sort of interesting work around that and reporting around that. I feel like, you know, SolarWinds created a new awareness. You know, you see these moments, it's stucks net or want to cry, and now SolarWinds is very insidious. But security, Red Hat, it's everywhere in your portfolio. Maybe talk about the strategy. Sure, absolutely. We feel strongly that it's really important that security be something that is managed in a holistic way, present throughout the application stack, starting with the operating system and also throughout the life cycle, which is partly where Dev SecOps comes in, right? So Red Hat has kind of had a long history here, right? I think SE Linux in Red Hat Enterprise Linux for mandatory access control, that's been a key component of securing containers in a Kubernetes environment. SE Linux has demonstrated the ability to prevent or mitigate container escapes to the file system. And we just have continued to work up the stack as we go. Our acquisition of Stack Rocks a little over a year ago, now known as Red Hat Advanced Cluster Security, gives us the opportunity to really deliver on that Dev SecOps component, both to Kubernetes native security solution with the ability to both help shift security left for the developers by integrating in the supply chain, but also providing a SecOps perspective for the operations and the security team and feeding information between the two to really try and do that closed infinity loop. And then an additional investment more recently in SIGStore and some technologies. Interesting, yeah, SIGStore, go ahead. But shift left, explain to people what you mean by shift left for people might not be familiar with that. Fair enough, so tradition, for many, many years, right? Security, IT security has been something that's largely been part of an operations environment and not something that developers tended to need to be engaged in with the exception of, say, static source code, static analysis tools. We started to see vulnerability management tools get added, but even then they tend to come after the application has been built. And I even ran a few years ago, I ran into a customer who said my security team won't let me get this information early. So shift left is all about making sure that there are security gates in the app dev process and information provided to the developer as early as possible, in fact, even in the IDE, Red Hat Code Ready dependency analytics does that, so that the developers are part of the solution and don't have to wait and get their app stalled just before it's ready to go into deployment. You've also been advocating for supply chain security, software supply chain, first of all, explain what a software supply chain is and then what is unique about the security needs of that environment? Sure, and the SolarWinds example, as Dave said, really kind of has raised awareness around this. So just like we use the term supply chain, most people given kind of what's been happening with the pandemic, they've started hearing that term a lot more than they used to, right? So there's a supply chain to get your groceries to the grocery store, food to the grocery store, there's a supply chain for manufacturing, where do the parts come for the laptops that we're all using, right? And where do they get assembled? Software has a supply chain also, right? So for years and even more so now, developers have been including open source components into the applications they build. So some of the supplies for the applications, the components of those applications, they can come from anywhere in the world, they can come from a wide range of open source projects, developers are adding their custom code to that, all of this needs to be built together, delivered together. And so when we think about a supply chain and the SolarWinds hack, right, there are a couple of elements of supply chain security that are particularly key. The executive order from May of last year, I think was partly in direct response to the SolarWinds hack, and it calls out that we need a software bill of materials. Now again, in manufacturing, that's something folks are used to. I actually had the opportunity to contribute to the software package data exchange format, SPDX, when it was first started, I've lost track of when that was. So but in SBOM is all about saying what are all of those components that I'm delivering in my solution, it might be an application layer, it might be the host operating system layer, but at every layer. And if I know what's in what I'm delivering, I have the opportunity to learn more information about those components to track, where does log for shell, right, when the log for J or spring for shell, which followed shortly thereafter, when those hit, how do I find out which solutions that I'm running have the vulnerable components in them and where are they? The software bill of materials helps with that, but you also have to know where, right? And that's the ops side. I feel like I missed a piece of your question. No, it's not a silver bullet, though, to your point and log for J very widely used, but let's bring Jim into the conversation. So Jim, we've been talking about some of these trends. What's your focus area of research? What are you seeing as some of the mega trends in this space? So yeah, I mean, I focus in DevOps and DevSecOps, and it's interesting just to talk about trends. Kirstin was mentioning the open source, and if you look back five, six, seven years ago, and you went to any major financial institution, you asked them if they use an open source. It's true. What do you think is that, right? Everything's, we wrote it all here, right? It's all from our developers, which were well done. Yeah, right, exactly. But the reality is they probably used an a little open source back then, but they didn't realize it, right? It's exactly true. However, today, not only are they not a versed open source, they're seeking it out, right? So we have survey data that kind of indicates, a survey that was run kind of in late 2021 that shows that 70% of those who responded said that within the next two years, 90% of their applications will be made up of open source. In other words, in other words, the content of an application, 10% will be written by themselves, and 90% will come from other sources. So we're seeing these more kind of composite applications, right? Not everybody's kind of, if you will, at that 90%, but applications are much more composite than they were before, right? So I'm pulling in pieces, but I'm taking the innovation of the community, right? So I not only have the innovation of my developers, but I can expand that, right? I can take the innovation of the community and bring that in and do things much quicker. I can also not have my developers worry about things that may be just kind of common stuff that's out there that might have already been written. In other words, just focus on the business logic. Don't focus on how to get orders or how to move widgets and those types of things that everybody does, because that's out there in open source. I'll just take that, right? I'll take it, somebody's perfected it, right? Better than I'll ever do. I'll take that in, and then I'll just focus and build my business logic on top of that. So open source has been a boom for growth, and I think we've heard a little bit of that in the last two days, right, from Red Hat, right? But talking about the software building materials, right? And then you think about now I'm taking all that stuff in, I have my first level open source that I took in, it's called Component A, but behind Component A is all these transitive dependencies. In other words, open source also uses open source, right? So there's this kind of this, if you will, web or nest, if you want to call it of transitive dependencies that need to be understood. And if I have five, six layers deep, I have a vulnerability in another component, and I'm over here, well, I guess what, I picked up that vulnerability, right? Even though I didn't explicitly go for that component. So that's where understanding that software building materials is really important. I like to explain it as, during the pandemic, we've all experienced, there was all this contact tracing, right? It was a term that all came to mind. The software building materials is like the contact tracing for your open source, right? Anything that I've come in contact with, just because I came in contact with it, even though I didn't explicitly go looking for COVID, if you will, I got it, right? So in the same regard, that's how I do the contact tracing for my software. That 90% figure is really striking. 90% of open source use is really striking, considering that it wasn't that long ago that one of the wraps on open source was it's insecure, because anybody can see the code, therefore anybody can create, can see the vulnerabilities. What changed? I'll say what changed is kind of first, the understanding that I can leapfrog and innovate with open source, right? There's more open source content out there. So as organizations had to digitally transform themselves, and we've all heard the terminology around, well, hey, you know, with the pandemic, we've leapfrog of five years of digital transformation or something along those lines, right? Open source is part of what helps those teams to do that type of leapfrog and do that type of innovation, right? If you had to develop all of that natively, it just takes too long, or you might not have the talent to do it, right? And to find that talent to do it. So it kind of gives you that benefit. The interesting thing about what you mentioned there was, you know, now we're hearing about all these vulnerabilities, right, and in open source, right, that we need to contend with because the bad guys realize that I'm taking a lot of open source and they're saying, geez, that's a great way to get myself into applications, right? If I get myself into this one open source component, I'll get into thousands or more applications, right? So it's a fast path into the supply chain and that's why it's so important that you understand where your vulnerabilities are and the software. I think the visibility cuts two ways, though. So when people say it's insecure because it's visible, in fact, actually the visibility helps with security. The reality that I can go see the code, that there is a community working on finding and fixing vulnerabilities in that code. Whereas in code that is not open source, it's a little bit more security by obscurity, which isn't really security and there could well be vulnerabilities that a good hacker is going to find, but are not disclosed. So one of the other things we feel strongly about at Red Hat, frankly, is if there is a CVE that affects our code, disclose that publicly. We have a public CVE database and it's actually really important to us that we share that. We think we share way more information about issues in our code than most other users or consumers of open source and we work that through the broad community as well. And then also for our enterprise customers, if an issue needs to be fixed, we don't just fix it in the most recent version of the open source, we will backport that fix. And one of the challenges, if you're only addressing the most recent version, that may not be well tested. It might have other bugs. It might have other issues. When we backport a security vulnerability fix, we're able to do that to a stable version, give the customers the benefit of all the testing and use that's gone on while also fixing. Kirsten, can you talk about the announcements? Because everyone's wondering, okay, now what do I do about this? What technology is there to help me? Obviously, in this framework, you got to follow the right processes, skill sets, all that, not to dismiss that, that's the most important part. But the announcements that you made at Red Hat Summit, and how does the Stack Rocks acquisition fit into those? Sure, so in particular, if we stick with DevSecOps a minute, but again, I'll do, it's not just, again, for me, DevSecOps is the full life cycle and many people think of it as just that shift left piece, but for me, it's the whole thing. So Stack Rocks ACS has had the ability to integrate into the CICD pipeline before we bought them, that continues. They don't just assess for vulnerabilities, but also for application misconfigurations, access priv requests and helm charts, deployment, YAML. So kind of the big, there are two sort of major things in the DevSecOps angle of the announcement or the supply chain angle of the announcement, which is the investment that we've been making in Sigstore, you know, signing, getting integrity of the components, the elements you're deploying is important. It's, I have been asked for years about the ability to sign container images. The reality is that the signing technology in Red Hat signs everything we ship and always have, but the signing technology wasn't designed to be used in a CICD pipeline, and Sigstore is explicitly designed for that use case to make it easy for developers, as well as, you know, you can back it with Fulcio, you can back it with an OIDC-based signing, keyless signing, throw away the key, or if you want that enterprise CA, you can have that backing there too. And you can establish that as a protocol where you must? You can, you can, right, so our pattern. So that would have helped with SolarWinds. Absolutely. Right, because they were putting in malware and then taking it out, seeing what happened. But that's my question was, could Sigstore help? I always evaluate now everything, and I'm not a security expert, but would this have helped with SolarWinds? A lot of times the answer is no. It's a combination. So a combination of Sigstore integrated with TectonChains. So we ship Tecton, which is a Kube-native supply chain pipeline. As OpenShift Pipelines, we added chains to that. Chains allows you to attest every step in your pipeline. And you're doing that attestation by signing those steps so that you can validate that those steps have not changed. And in fact, the folks at SolarWinds are using TectonChains. They did a great talk in October at KubeCon North America on the changes they've made to their supply chain. So they are using both TectonChains and Sigstore as part of their updated pipeline. Our pattern will allow our customers to deploy OpenShift Advanced Cluster Manager, Advanced Cluster Security and Quay with security gates in place and that include a pipeline built on Tecton with TectonChains there to sign those steps in the pipeline, to enable signing of the code that's moving through that pipeline, to store that signature in Quay and to validate the image signature upon deployment with Advanced Cluster Security. So, Jim, your perspective on this. So Red Tats, I mean, you care about security, security is everywhere, but you're not a security company. You follow security companies. There's like far too many of them. CISOs all say my number one challenge is lack of talent, but I have all these tools to deal with. You see new emerging companies that are, you know, doing pretty well and then you see a company that's highly respected like an octa screw up the communications on a pretty benign hack actually when you peel the onion on that. It's just this mess and it doesn't seem like it's going to get any simpler. Maybe the answer is companies like Red Hat kind of absorbing that and taking care of it. What do you see there? I mean, maybe it's great for business because you've got so many companies. Yeah, there's a lot of companies and there's certainly a lot of innovation out there and unique ways to make security easier, right? I mean, one of the keys here is to be able to make security easier for developers, right? You know, one of the challenges with adopting DevSecOps is if DevSecOps creates a lot of friction in the process, right? It's hard to really, you know, I can do it once but I can't keep doing that, right? And get the same kind of velocity, right? So I need to take the friction out of the process. And one of the challenges a lot of organizations have and I've heard this from the development side but I've also heard it from the infosex side, right? Because, you know what, I take inquiry for people in infosex and they're like, how do I get these developers to do what I want, right? You know, part of the challenge they have is like, you know, I got these teams using these tools, I got those teams using those tools. And it's a similar challenge that we saw on DevOps where there's just too many, if you will, too many dang tools, right? So, you know, that is a challenge for organizations is they're trying to kind of normalize the tools. Interestingly, we did a survey, I think around last August or something and one of the questions was around, you know, where do you want your security, right? Where do you want to get your DevSecup security from? Do you want to get it from individual vendors, right?  Great question, Kubernetes. What would they say? The majority of them, they're hoping they can get it built into the platform. That's really what they want. They want it, and it's, you know, and you see a lot of the security vendors are trying to build security platforms. Like we're not just a SaaS tool, we're DAS, we're this, you know, whatever, right? You know, and they're building platforms to kind of be that end to end security platform. Trying to solve that problem, right? To, you know, make it easier to kind of consume the product overall, you know, without a bunch of individual tools along the way. But certainly, tool sprawl is definitely a challenge out there. Just one other point around the six store stuff, which I love, because, you know, that goes back to the supply chain and talking about digital provenance, right? Understanding where things, how do I validate, you know, that what I gave you is what you thought it was, right?  Well, first of all, you know, I don't want to just sign things like after I built the binary. Well, I mean, I do want to sign it, but I don't want to just sign things once, right? Because all through the process, you know, think of it as a manufacturing plant, right? I'm making automobiles, right? If I check the quality of the automobile at one stage and I don't check it to the other, you know, things have changed, right? How do I know that I did something wasn't compromised, right? So with six store kind of tied in with Tecton Chains, you know, it kind of gives me that view. And the other aspect I like about it is, you know, kind of this kind of transparency in the law, right? To understand, right, exactly. So I could see what was going on. So there is some this kind of like public scrutiny, like if something bad happened, you could go back and see what happened there and it wasn't as you expected, right? As with most discussions on this topic, we could go for an hour. Right, I know. Yes, that's really important. And thank you guys for coming on, sharing your perspectives, the data. Our pleasure. Keep up the good work, Kirsten. Yeah, thanks so much. It's on you. Yeah. The IDC survey said it, they want it. That's right. They want it in platforms.  That's right. That's right. All right, good luck to both of you. Great, thank you both so much. All right, and thank you for watching. We're back to wrap right after this short break. This is Dave Vellante for Paul Gillin. You're watching The Cube.


Hello everyone, here is your day and today I just want to talk to you about an interview in which I took part a few days ago.  I think that I was a month ago, but I'm not sure about that. It doesn't matter. And then I found a new job in Antopreno, which is very close to my house. In fact, I can't go there, it's so close. And the living room is much higher, and the living room itself is much higher, so I'm very happy about that. Also, there's a problem. After three weeks of work, I noticed that almost everyone around me doesn't want to have a career. They just want to work in the same living room while the whole life, without moving. And I'm not one of those people. I always want to learn. I always want to move. I always want to say, no, I just want to talk. I always want to. So, of course, the future doesn't seem that way for me. And I started to feel like I'm a new entrepreneur without thinking, I suppose. But one of the entrepreneurs actually responded, and it's a very televised entrepreneur. And I really like to have a job in Antopreno. Because I really like the film industry, so I really want to take part in it. And they invited me to the interview a week ago, and it seems that everyone was surprised, because in fact, they want to interview me again. And that happened today. Here's the topic of this video blog. And the interview took place on Skype, because one of the entrepreneurs came to Singapore and the other to Sydney, in fact. So, it doesn't matter. And everything went well, for maybe 30 minutes. But then something bad happened. One of the interviewers said to me, very comfortably and without thinking, so you have a YouTube channel, don't you? And I thought, well, I didn't write that in my Vip protocol. Oh, well, did he expect it? Oh, well, why? Probably he googled my name and later found that I have a YouTube channel. But I didn't put my real name in my YouTube channel. How could he expect my films? And he could read my thoughts. He said, you are very energetic, full of people. And I said, I suppose that I'm a little confused about things that I like. And then I have to wait a few moments, when he did it. And I wanted to say something. And then he said, we need something that is very energetic, because our clients need that. So I thought that you would be very happy about this.  Because I was very happy about that. Now I thought that maybe he saw my channel and said, oh, fuck!   My heart just stopped for a moment. I almost had a heart attack, I suppose. But it seems that everything is clear. And later he said, I never thought that people would speak Esperanto. Because I thought that he died many years ago than all English speakers. And not the English speakers. They didn't die, but he thought the same as all English speakers. And then I started to relax more and more. And the interview continued without any problems. And everything went wrong again. And later he said, Thank you, we will send you a message next week if we want to move forward. And I said, Hmm, good, good. I actually want to move forward. And I suppose that if you want to know what happens, just write a comment below and I will tell you if I am getting it or just joking about the whole thing. It doesn't matter. But I just wanted to share this strange moment with you. Because you are my viewers. And I feel like you are with me on this journey to nowhere. I don't know. So if you liked this movie, like it, share it, subscribe to my channel if you haven't subscribed yet. And I will see you in the next movie. And if you are not there, I will find you. And I hope that you are not the only one who knows my name. And I hope that you are my first and last. No.


The Watercycle Multimission Observation Strategy Evapotranspiration, WACMOS-ET, project aims to advance the development of land evaporation estimates on global and regional scales. It seeks to derive, validate, and compare existing evaporation retrieval algorithms driven by a common forcing dataset. Three commonly used process-based evaporation methodologies will be evaluated, Penman-Monteith algorithm behind the official Modi's evaporation product, PMMOD, the Global Land Evaporation Amsterdam Model, GLEAM, and the Priestley-Taylor Jet Propulsion Laboratory Model, PTGPL. The resulting global spatiotemporal variability of evaporation, the closure of regional water budgets, and discrete estimation of land evaporation components or sources, transpiration, interception loss, and direct soil evaporation will be investigated using river discharge data, independent global evaporation datasets, and results from previous studies. Additionally, Michelle et al., 2016, assessed the performance of these three models at local scales using measurements from eddy covariance towers and included in the assessment to This article was authored by D. G. Mirales, C. Jimenez, M. Jung, and others. We are article.tv, links in the description below.