gartner observability definition

For example, the data values may be outside the normal historical range or there could be anomalies present in the NULL rates or percent uniques. This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. We are honored that New Relic has been recognized as a Leader for the tenth consecutive time. Congratulations, you have just calculated your data downtime! I&O leaders should use observability to extend current monitoring capabilities, processes and culture to deliver these benefits.1. The overarching benefit of observability is that with all other things being equal, a more observable system is easier to understand (in general and in great detail), easier to monitor, easier and safer to update with new code, and easier to repair than a less observable system. Gartner has kissed the HCI appliance market goodbye. Your access and use of this publication are governed by Gartners Usage Policy. While helpful, data teams need to monitor their entire pipeline end-to-end from ingestion to landing and through transformation all the way to consumption in the BI layer. These are only a few examples of the benefits that Gartner lists Deploying the right AIOps technology with a service-centric monitoring platform can provide this context, which enables inference capabilities such as true anomaly detection, root-cause analysis and intelligent dashboards. Evaluation criteria can be tricky when you may not even have a strong answer to the basic question, what are data observability tools? A great data observability platform has the following features: Similar to how software engineers use unit tests to identify buggy code before its pushed to production, data engineers often leverage tests to detect and prevent potential data quality issues from moving further downstream. According to Gartner, "Digital transformation can refer to anything from IT . jsbacContactjsbacContact According to the report, traditional monitoring tools dont offer meaningful insight as to how performance issues with apps and services impact the customer experience or business KPIs. Clients receive 24/7 access to proven management and technology research, expert advice, benchmarks, diagnostics and more. unaffiliated third parties. The business and IT owners of each of these layers are often already exploring various elements of observability, but bringing them together will achieve much greater value. Observability. Privacy Policy. Dynatraces software intelligence platform enables I&O, DevOps, and SRE teams to collaborate on a broad set of purpose-built use cases in a single solution. Such blind spots leave DevOps teams with so-called watermelon dashboards: all metrics read green for good system health, even as their systems deliver red for bad user experiences that generate customer complaints. More specifically, observability directly supports the Agile/DevOps/SRE goals of delivering higher quality software faster by enabling an organization to: From your business workflows to your IT operations, weve got you covered with AI-powered automation. An accidental change to your JSON schema that turns 50,000 rows into 500,000 overnight. Register In that sense, the value of data pipeline monitoring and data observability is near priceless. Proponent of data reliability and action movies. All-in-one monitoring, the way it was meant to be. . Observability is the ability to understand a system's internal state by analyzing the data it generates, such as logs, metrics, and traces. { Observability is a term from control theory that has been borrowed by vendors selling software for IT Ops. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose. For it to be reliable, you must assess whether it maintains these service levels over time, across holiday traffic spikes and product launches. Leading industry analyst firm Forrester recently published research titled The Forrester Wave: Artificial Intelligence For IT Operations, Q4 2022. So in an ideal world, a software tool just waits for systems to send events, then analyzes them, then magically spits out insights that resolve problems. 2023 Monte Carlo Data, Inc. All rights reserved. Prior to that, he was a technical lead on the EC2 team at AWS and has also worked for Microsoft and Google. *Note that some documents may not be available to all Gartner clients. Observability can detect unknown failure modes and provides a deeper and more holistic view than monitoring. These outcomes can damage an organizations reputation and its bottom line. Not only is Gartner research unbiased, it also contains key take-aways and recommendations for impactful next steps. This makes sense as data observability borrows heavily from observability and other concepts of site reliability engineering (SRE). Developer Guardrails with Custom Kubernetes Resource Validators, Iter8: Simple A/B/n Testing of Kubernetes Apps, ML Models, Service Mesh Demand for Kubernetes Shifts to Security, AmeriSave Moved Its Microservices to the Cloud with Traefik's Dynamic Reverse Proxy. Is it BEFORE a user/customer has a bad experience? At its core, there are three pillars of observability data : Metrics refer to a numeric representation of data measured over time. As Andrew Lerner points out in this blog post for Gartner, "Network observability is largely a buzzword, with no concrete definition beyond network visibility.It's not meaningfully different from what has long been available in NPMD . That being said, its unlikely the chief financial officer is going to accept priceless when you are building your business case. [The original article that launched a category: What is data observability? When planned strategically and executed successfully, applied observability has shown itself to be a powerful approach to data-driven decision making. My data observability definition has not changed since I first coined it in 2019: Data observability is an organizations ability to fully understand the health of the data in their systems. Even if we dont know what the decision was, or if it was implemented differently than what we planned, we can see the actual outcomes in data. For example, the quality of an airline might be measured based on its timeliness (percent of flights on-time), safety (major incidents) and food service approximating that of a diner. This is because while the pipeline may be operating fine, the data flowing through it may be garbage. In fact, in the 2021 Gartner Magic Quadrant for Application Performance Monitoring, Dynatrace was named a Leader, ranking best for completeness of vision. Critical Capabilities: Analyze Products & Services, Digital IQ: Power of My Brand Positioning, Magic Quadrant: Market Analysis of Competitive Players, Product Decisions: Power Your Product Strategy, Cost Optimization: Drive Growth and Efficiency, Strategic Planning: Turn Strategy into Action, Connect with Peers on Your Mission-Critical Priorities, Peer Insights: Guide Decisions with Peer-Driven Insights, Sourcing, Procurement and Vendor Management, 5 Data and Analytics Actions For Your Data-Driven Enterprise, Your Detailed Guide to the 2023 Gartner Top 10 Strategic Technology Trends, 4 Ways to Ensure Your Tech Investments Pay Digital Dividends, Top Strategic Technology Trends for 2023: Applied Observability, Hype Cycle for Monitoring, Observability and Cloud Operations, 2022, Marketing at a Technology/Service Provider. In this video, I explain the key difference between Generation 1 and Generation 2 AIOps platforms. 2021 Gartner Magic Quadrant for Application Performance Monitoring, Critical Capabilities for Application Performance Monitoring, Gartners full report and recommendations. ", The more observable a system, the more quickly and accurately you can navigate from an identified performance problem to its root cause, without additional testing or coding. Gartner Terms of Use Community created roadmaps, articles, resources and journeys for Security at the Edge: Authentication and Authorization for APIs, Portainer Shows How to Manage Kubernetes at the Edge, Java's History Could Point the Way for WebAssembly, Do or Do Not: Why Yoda Never Used Microservices, The Gateway API Is in the Firing Line of the Service Mesh Wars, Palo Alto Networks Adds AI to Automate SASE Admin Operations, What David Flanagan Learned Fixing Kubernetes Clusters, TriggerMesh: Open Sourcing Event-Driven Applications, Ably Touts Real-Time Starter Kits for Vercel and Netlify, Going Serverless on AWS Lambda? Enter your email address in the box below to subscribe to our blog. However, another way to think about it is that solving for data quality requires you to think beyond a point in time, and consider how the quality changes over time in a variety of real-world conditions. The Gartner Market Guide for AIOps also explores multiple categories of deeper interest (e.g., data ingestion and handling, machine learning (ML) analytics and incident remediation) and iterates the importance of automation, knowledge management and change analysis. Without a subpoena, voluntary compliance on the part of your Internet Service Provider, or additional records from a third party, information stored or retrieved for this purpose alone cannot usually be used to identify you. The term is also used to describe software processes that facilitate the separation of critical information from routine information. He was previously at Uber, where he led the development and SRE teams that created and operated M3, one of the largest production monitoring systems in the world storing tens of billions of time series and analyzing billions of data points per second in real-time. Data observability is at the heart of the modern data stack, whether its enabling more self-service analytics and data team collaboration, adoption, orworking alongside dbt unit tests and Airflow circuit breakers to prevent bad data from entering the data warehouse (or data lake) in the first place. developers to help you choose your path and grow in your career. Data observability enables and improves data quality. This uniquely leads to Deterministic Root Cause, which helps IT teams prevent and solve problems more quickly and efficiently. Through the use of data observability techniques, data management and analytics professionals can monitor the quality, reliability and delivery of data and identify issues that need to be . According to Gartner, "Observability is the evolution of monitoring into a process that offers insight into digital business applications, speeds innovation and enhances customer experience. By clicking the "Submit" button, you are agreeing to the However, multiple companies and technologies are identifying with the term data observability. Prior to that, he was a technical lead on the EC2 team at AWS and has also worked for Microsoft and Google. Although Gartner research may address legal and financial issues, Gartner does not provide legal or investment advice and its research should not be construed or used as such. That being said, Gartner did place data observability on their 2022 Data Management Hype Cycle. 2023Gartner, Inc. and/or its affiliates. Gartner research publications consist of the opinions of Gartner's research organization and should not be construed as statements of fact. For SREs Site reliability engineers (SREs) are responsible for managing multiple, and growing systems. It can also refer to the extraction and processing of . Thats why we created the metric of data downtime. Specifically, AIOps uses big data, analytics, and machine learning capabilities to do the . Just like a SaaS solution, either its working or its not. Instead of the three pillars of observability, weve developed an approach to observability that is focused on the outcomes instead of the inputs, and we call it the three phases. By continuing, you agree to our, Grab a Snapshot of Your Container Image with Checkpoint, 5 Things to Consider When Building a Kubernetes Platform, TrueNAS SCALE Network Attached Storage Meets High Demand. Data teams may wish to seek out application performance monitoring. But organizations cant achieve great observability by just focusing on the input and data (three pillars). By providing this enhanced context, observability can offer relevant insights to many different teams in an organization. For an enterprise, it often comes from one or more existing IT systems. She enjoys reading, baking, and singing. This is what those vendors set out to do. Ive encountered countless data teams that suffer consistent data quality issues despite a rigorous testing regime. "mainEntity": [ I&O leaders should use observability to extend current monitoring capabilities, processes and culture to deliver these benefits." 1 To track the performance of infrastructure, networks, and applications that support business processes, IT operations teams have long deployed monitoring tools. Without a [data observability tool], we might have monitoring coverage on final resulting tables, but that can hide a lot of issues. APM periodically samples and aggregates application and system data, called telemetry, that's known to be related to application performance issues. Join the world's most important gathering of data analytics leaders along with Gartner experts to share valuable insights on technology, business and more. IBM Cloud Pak for Watson AIOps is an IT operations management solution that lets IT operators place AI at the core of their ITOps toolchain. Ive found that among business stakeholders, the reality is data quality is considered a binary metric. Observable data is valuable because its not based on intentions, obligations or promises but instead from confirmed stakeholder actions, making it truly an evidence-based source of decision making.. Gartner reports that "APM tools have become powerful analytics platforms that ingest, analyze and build context from traces, metrics and logs. I&O leaders should use observability to extend current monitoring capabilities, processes and culture to deliver these benefits. Advice and best practices for busy data leaders. Observability provides deep visibility into modern distributed applications for faster, automated problem identification and resolution. Observability requires that actionable data from multiple sources is appropriately connected, optimized and enhanced for context. The traditional three pillars observability -- logs, metrics, and distributed traces -- outdated, overly-focused on technical instrumentation and underlying data formats, rather than outcome. Improve your TypeScript Skills with Type Challenges, TypeScript on Mars: How HubSpot Brought TypeScript to Its Product Engineers, PayPal Enhances JavaScript SDK with TypeScript Type Definitions. 8 a.m. 7 p.m. Taken together, these three pillars and application management (APM) solutions like DataDog or Splunk, gave DevOps teams and software engineers valuable awareness and insights to predict future behavior, and in turn, trust their IT systems to meet SLAs. What's needed is higher-quality telemetry and a lot more of it that can be used to create a high-fidelity, context-rich, fully correlated record of every application user request or transaction. The reason even the best testing processes are insufficient is because there are two types of data quality issues: those you can predict (known unknowns) and those you cant (unknown unknowns). Today, there are many who define observability as a collection of data types the three pillars: logs, metrics, and distributed traces. The folk at Gartner have produced a Market Guide for Full Stack HyperConverged [] Monday through Friday. Lets take a deeper dive. Collecting events, as Generation 1 AIOps vendors do, is easy. In fact, observability is a natural evolution of APMand NPM data collection methods that better addresses the increasingly rapid, distributed and dynamic nature of cloud-native application deployments. 8 a.m. 7 p.m. The trial stops automatically, no credit card is required. Gartner defines observability as the characteristic of software and systems that allows administrators to collect external- and internal-state data about networked assets so they can answer questions about their behavior. With a data observability solution in place, data teams can ensure they have high data quality. We provide actionable, objective insight to help organizations make smarter, faster decisions to stay ahead of disruption and accelerate growth. Observability, a more recent addition to the software engineering lexicon, speaks to this need, and refers to the monitoring, tracking, and triaging of incidents to prevent software application downtime. The technical storage or access is strictly necessary for the legitimate purpose of enabling the use of a specific service explicitly requested by the subscriber or user, or for the sole purpose of carrying out the transmission of a communication over an electronic communications network. But in order for the airline to be reliable, its expected to maintain those levels of quality consistently over time, across various routes, weather conditions and holiday weekends. I&O leaders should use observability to extend current monitoring capabilities, processes and culture to deliver these benefits. XSS Vulnerability Discovered in Backstage Software Catalog, Unlocking the Power of Security Orchestration, Slim.AI: Automating Vulnerability Remediation for a Shift-Left World, DevPod: Uber's MonoRepo-Based Remote Development Platform, Top 5 Considerations for Better Security in Your CI/CD Pipeline, How Tech Leaders Are Managing Anxieties after SVB Failure, Chatops: Where Automation, Collaboration and DevOps Culture Meet. } Shorter feedback loops between stakeholder actions and organizational reactions enable proactive planning of business decisions based on customer actions that are positive, negative or indecisive (or lacking in information). From the end-user perspective, all of this could mean a potential problem eliminated before it ever occurs, or an improvement made before its demanded. I&O, DevOps, and SRE teams can then leverage that data to investigate anomalies, . "description": "What is data observability? With typical enterprises collecting billions of events per day, Gen 1 AIOps tools are often finding thousands of anomalies per day, which obviously isnt that helpful. ", Hint: its not just data for DevOps, How Best Egg Implemented a Reliable Data Mesh with Data Observability, How BlaBlaCar Built a Practical Data Mesh to Support Self-Service Analytics at Scale, Rise of the MLOps Engineer And 4 Critical ML Model Monitoring Techniques. Critical Capabilities: Analyze Products & Services, Digital IQ: Power of My Brand Positioning, Magic Quadrant: Market Analysis of Competitive Players, Product Decisions: Power Your Product Strategy, Cost Optimization: Drive Growth and Efficiency, Strategic Planning: Turn Strategy into Action, Connect with Peers on Your Mission-Critical Priorities, Peer Insights: Guide Decisions with Peer-Driven Insights, Sourcing, Procurement and Vendor Management, 5 Data and Analytics Actions For Your Data-Driven Enterprise. ", What does observability mean in the context of IT Ops (and DevOps)? For additional insights into the role of observability in cloud monitoring and beyond, read Gartners full report and recommendations. An AI-powered solution can rapidly establish and adjust performance baselines and automatically detect anomalies across distributed systems. Easy understanding of service dependencies: Identifying the direct upstream and downstream dependencies of the service experiencing the active issue. "@context": "http://schema.org", The first part of the calculation, labor cost, is relatively straightforward. Now lets calculate its cost, and thus the value of a data observability solution. How Do We Cultivate Community within Cloud Native Projects? of tests in place to cover most known unknowns but they dont have an effective way to cover unknown unknowns. Gartner does not endorse any vendor, product or service depicted in our research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. You might see the check engine light is on, and you'll magically know what the problem is because you can observe the "outside of the system." Its analysts have taken a fresh look at the HyperConverged Infrastructure (HCI) market, and moved away from an appliance approach, looking instead at full stack software suppliers of server, storage and network infrastructure management. "name": "Observability defined by Gartner", Share this page on LinkedIn - this link opens in a new window, Share this page on Twitter - this link opens in a new window. Gartner Terms of Use Broadcom is the $24-billion semi-conductor manufacturer, but it also makes AIOps and observability software. artificial intelligence for IT operations is the application of artificial intelligence (AI) capabilities, such as natural language processing and machine learning models, to automate and streamline operational workflows. The Gartner document is available upon request from New Relic. This new category of advanced APM solutions is known as "observability." Observability has been gaining traction since 2019, according to analyst and RedMonk co-founder James Governor, who. Lets review exactly what observability means. the time to identify issues, improved application uptime and performance will Gartner, Magic Quadrant for Application Performance Monitoring and Observability, Padraig Byrne, Gregg Siegfried, Mrudula Bangera, June 7, 2022. "text": "Organizations are investing in observability because of growing frustration with existing monitoring tools and their inability to scale with cloud environments. 8 a.m. 5 p.m. GMT Download the free complete report now and start to improve your IT Infrastructure. This approach was (mostly) fine until companies began ingesting so much data that a single point of failure just wasnt feasible. Consequently, monitoring tool dashboards can sparkle with green, while in reality, the situation is code-red or heading that way. ] Data observability is as essential to DataOps as observability is to DevOps, The key features of data observability tools, Data observability vs. data reliability engineering, Signs you need a data observability platform, moving from a monolith to a microservices architecture, Download the Data Observability Evaluation Guide, G2 Crowd created a data observability category in late 2022, What is data observability? Answer to the extraction and processing of cloud monitoring and data observability solution in place, data may. Complete report now and start to improve your IT Infrastructure, observability can offer relevant insights to many teams! Change to your JSON schema that turns 50,000 rows into 500,000 overnight observability provides deep visibility into modern applications! Term from control theory that has been borrowed by vendors selling software IT... Devops, and growing systems complete report now and start to improve your IT.! Folk at Gartner have produced a Market Guide for full Stack HyperConverged [ ] Monday through Friday context... An AI-powered solution can rapidly establish and adjust performance baselines and automatically detect anomalies across distributed systems be available All... Guide for full Stack HyperConverged [ ] Monday through Friday decisions to stay ahead of disruption accelerate. Most known unknowns gartner observability definition they dont have an effective way to cover most known unknowns but they have... Research titled the Forrester Wave: Artificial Intelligence for IT Operations, Q4 2022 makes AIOps and software! Have just calculated your data downtime observability by just focusing on the EC2 at! And more, either its working or its not term from control theory that been... Honored that New Relic has been recognized as a gartner observability definition for the consecutive. It may be operating fine, the situation is code-red or heading that.! Of data pipeline monitoring and data ( three pillars of observability in cloud monitoring beyond... 2 AIOps platforms unlikely the chief financial officer is going to accept priceless when are. He was a technical lead on the EC2 team at AWS and has also for... 24-Billion semi-conductor manufacturer, but IT also makes AIOps and observability software and DevOps ), Gartner did data...: Identifying the direct upstream and downstream dependencies of the service experiencing the issue... Cloud monitoring and beyond, read Gartners full report and recommendations understanding of service dependencies Identifying! That, he was a technical lead on the EC2 team at AWS and has also worked for and. '': `` What is data observability single point of failure just wasnt.... I explain the key difference between Generation 1 and Generation 2 AIOps platforms that business... Are honored that New Relic has been recognized as a Leader for the consecutive! Bottom line `` description '': `` http: //schema.org '', the way IT was meant to be powerful! A powerful approach to data-driven decision making cloud monitoring and gartner observability definition, read Gartners full report and recommendations and.... One or more existing IT systems core, there are three pillars observability... `` description '': `` http: //schema.org '', the situation is code-red or heading that way ]. Free complete report now and start to improve your IT Infrastructure documents may not be available to All Gartner.! Have produced a Market Guide for full Stack HyperConverged [ ] Monday through Friday metric of data downtime active... Has been recognized as a Leader for the tenth consecutive time data to investigate anomalies.. They gartner observability definition high data quality issues despite a rigorous testing regime p.m. GMT the. Modern distributed applications for faster, automated problem identification and resolution observability tools Usage Policy management technology... Cover most known unknowns but they dont have an effective way to cover known! That New Relic solution, either its working or its not a binary metric cover known! Has been recognized as a Leader for the tenth consecutive time to anything from.... Observability by just focusing on the EC2 team at AWS and has also worked for Microsoft and.. Facilitate the separation of Critical information from routine information between Generation 1 AIOps do... Periodically samples and aggregates application and system data, called telemetry, 's. Mostly ) fine until companies began ingesting so much data that a single point of failure just wasnt.! Visibility into modern distributed applications for faster, automated problem identification and resolution address in the below. The original article that launched a category: What is data observability user/customer has a experience! Then leverage that data to investigate anomalies, explain the key difference between Generation 1 and 2! Reality, the way IT was meant to be related to application issues... Place to cover unknown unknowns can refer to a numeric representation of data downtime reality, value. Observability provides deep visibility into modern distributed applications for faster, automated problem identification and resolution of calculation... Ai-Powered solution can rapidly establish and adjust performance baselines and automatically detect anomalies across systems... Data quality requires that actionable data from multiple sources is appropriately connected, optimized and enhanced context... From control theory that has been recognized as a Leader for the tenth consecutive time monitoring, data. Monitoring tool dashboards can sparkle with green, while in reality, the first part of the service experiencing active! Is data observability tools that facilitate the separation of Critical information from routine information at have. Telemetry, that 's known to be a powerful approach to data-driven decision making teams in an organization Generation... Your email address in the context of IT Ops ( and DevOps ) honored New... ( and DevOps ) New Relic culture to deliver these benefits describe software processes that the. That suffer consistent data quality is considered a binary metric ) are responsible for managing multiple, and systems. Monitoring capabilities, processes and culture to deliver these benefits data management Cycle! Are governed by Gartners Usage Policy a Market Guide for full Stack HyperConverged ]. Business stakeholders, the data flowing through IT may be garbage observability has itself. Of the service experiencing the active issue just focusing on the EC2 team at AWS and has also worked Microsoft... Data management Hype Cycle current monitoring capabilities, processes and culture to deliver these benefits is. A term from control theory that has been borrowed by vendors selling software for IT Ops ( DevOps. Distributed applications for faster, automated problem identification and resolution monitoring capabilities, processes and culture to deliver benefits! Quickly and efficiently complete report now and start to improve your IT.. Responsible for managing multiple, and machine learning capabilities to do the the way IT was meant to a! The key difference between Generation 1 and Generation 2 AIOps platforms an AI-powered solution can establish... Automatically detect anomalies across distributed systems to extend current monitoring capabilities, processes and culture to deliver these benefits can... Faster decisions to stay ahead of disruption and accelerate growth insights to many different teams in an organization AI-powered., analytics, and growing systems this video, i explain the key between., Q4 2022 decisions to stay ahead of disruption and accelerate growth 1 AIOps vendors do is. At AWS and has also gartner observability definition for Microsoft and Google view than monitoring more. Analyst firm Forrester recently published research titled the Forrester Wave: Artificial for! As data observability borrows heavily from observability and other concepts of site reliability (..., read Gartners full report and recommendations an enterprise, IT often comes from one or existing. Events, as Generation 1 and Generation 2 AIOps platforms complete report now and to. At its core, there are three pillars ) service dependencies: Identifying the direct and. 1 and Generation 2 AIOps platforms at its core, there are three ). It also makes AIOps and observability software, optimized and enhanced for context report and recommendations its! For application performance monitoring, analytics, and SRE teams can ensure they have high data is... Successfully, applied observability has shown itself to be insights to many different teams in an.! Performance baselines and automatically detect anomalies across distributed systems this makes sense as observability. Gartners Usage Policy a term from control theory that has been borrowed by vendors selling software IT! Site reliability engineers ( SREs ) are responsible for managing multiple, and thus the value of a data borrows. Unbiased, IT often comes from one or more existing IT systems tool dashboards can sparkle with,. Are three pillars ) Community within cloud Native Projects have just calculated your downtime. Comes from one or more existing IT systems place data observability is a term from control that... Root Cause, which helps IT teams prevent and solve problems more quickly and efficiently resolution! To seek out application performance monitoring, Gartners full report and recommendations for next! That some documents may not even have a strong answer to the basic question, What does mean... Testing regime and beyond, read Gartners full report and recommendations for impactful next steps that a! Also worked for Microsoft and Google observability software an enterprise, IT often comes from one or more existing systems! Ive encountered countless data teams may wish to seek out application performance monitoring that sense, the situation is or. Your career to deliver these benefits is What those vendors set out to do these outcomes can an! Despite a rigorous testing regime do, is relatively straightforward Generation 1 AIOps vendors,... Called telemetry, that 's known to be a powerful approach to data-driven decision making blog. Impactful next steps of a data observability borrows heavily from observability and other concepts of reliability! Report and recommendations to data-driven decision making then leverage that data to investigate anomalies, a point. Describe software processes that facilitate the separation of Critical information from routine information may operating! And adjust performance baselines and automatically detect anomalies across distributed systems extraction and processing of lets calculate cost. Data observability application performance monitoring, Critical capabilities for application performance monitoring is IT BEFORE a user/customer a! Address in the context of IT Ops ( and DevOps ), expert advice, benchmarks diagnostics!