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How to Move from Monitoring to Observability, On-Premises and in a Multi-Cloud Environment
The document discusses the transition from monitoring to observability in IT operations, emphasizing the importance of understanding system behavior and addressing challenges in multi-cloud environments. It highlights how observability can improve IT operations by enabling real-time analysis, root cause investigation, and better team collaboration. Splunk's capabilities in handling machine data for enhanced visibility and decision-making are also outlined.
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Presentation by Dr. Siyka Andreeva and Marc Serieys. Discusses forward-looking statements regarding observability.
Definitions and challenges of observability. Distinction from monitoring. Importance in distributed systems.
Explores impact of multi-cloud and microservices architecture on customer experience and operational visibility.
Introduction to Splunk's tools for IT operations management and advantages in handling machine data.
Challenges in structuring machine data. Techniques for effective data collection, clustering, and anomaly detection.
Explaining knowns and unknowns in observability. Real-time analysis and predictive analytics through Splunk.
Wrap-up of the presentation. Thank you note.
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How to Move from Monitoring to Observability, On-Premises and in a Multi-Cloud Environment
- 1. © 2018 SPLUNKINC.© 2018 SPLUNK INC. How to Move From Monitoring to Observability Observability: the disingenuous rebranding of monitoring? Dr. Siyka Andreeva | IT Operations Analytics Specialist Marc Serieys | Staff Sales Engineer June 2019
- 2. © 2018 SPLUNKINC. Forward Looking Statements During the course of this presentation, we may make forward-looking statements regarding future events or the expected performance of the company. We caution you that such statements reflect our current expectations and estimates based on factors currently known to us and that actual events or results could differ materially. For important factors that may cause actual results to differ from those contained in our forward-looking statements, please review our filings with the SEC. The forward-looking statements made in this presentation are being made as of the time and date of its live presentation. If reviewed after its live presentation, this presentation may not contain current or accurate information. We do not assume any obligation to update any forward-looking statements we may make. In addition, any information about our roadmap outlines our general product direction and is subject to change at any time without notice. It is for informational purposes only and shall not be incorporated into any contract or other commitment. Splunk undertakes no obligation either to develop the features or functionality described or to include any such feature or functionality in a future release. Splunk, Splunk>, Listen to Your Data, The Engine for Machine Data, Splunk Cloud, Splunk Light and SPL are trademarks and registered trademarks of Splunk Inc. in the United States and other countries. All other brand names, product names, or trademarks belong to their respective owners. © 2017 Splunk Inc. All rights reserved.
- 3. © 2018 SPLUNKINC. Agenda What is observability ? And how it differs from monitoring? Why is observability even a bigger challenge in a multi-cloud and containerized world? How Splunk can help?
- 4. © 2018 SPLUNKINC. What is Observability? the disingenuous rebranding of monitoring ? monitoring on steroids? DevOpsifying monitoring?
- 5. © 2018 SPLUNKINC. Observability…the word starts spreading because failure is shifting to application code and in production system behavior
- 6. © 2018 SPLUNKINC. Why the word starts spreading ? IT Operations monitoring challenges are getting worth in a distributed world: • IT teams know that something is not working -- but not exactly why it’s not working • Repetitive, manual processes for reactive troubleshooting • Inability to get to root cause quickly • Siloed analysis of logs, traces, and metrics Management Expectations: • Avoid financial impact from fewer system outages • Accelerate investigation of application performance and system incidents with real-time log and metric analysis • Consolidate operational tools and/or external services into one observability tool • Improve collaboration across teams with targeted alerting and tailored visualization increases collaboration across teams Same for Dev teams: • Gap between perception and the reality • Dev teams spending too much time observing the dev and pre prod env and not prod
- 7. © 2018 SPLUNKINC. Why observability (in IT) ? Source Wikipedia Survivorship bias or survival bias is the logical error of concentrating on the people or things that made it past some selection process and overlooking those that did not, typically because of their lack of visibility. This can lead to false conclusions in several different ways. Shot down aircraft don’t externalize their state
- 8. © 2018 SPLUNKINC. in Software Systems Input Output What is observability? Flow Valv Purity Velocity Direction Quality Physical Telemetry in Industrial Systems Customer ID Success/Fail $ Spend Add to cart Checkout Bill/Ship Logging, Metrics Functions
- 9. © 2018 SPLUNKINC. From monitoring to the three (only three?) pillars of Observability Inspired from © @copyconstruct Symptoms (what’s broken?) Monitoring Alerting Service health Overview Investigation Allthetime Passive Ops Causes (why?) Debugging Profiling (system behavior) Dependency analysis (distributed systems tracing infrastructure) Observability Onthefly Reactive Dev Events ProfilesPillar A Pillar B Pillar C Pillar D LOGS METRICS TRACES
- 10. © 2018 SPLUNKINC. Why is that important in a multi-cloud environment? 2019 trends Business Logic Monolithic Architecture Billing Driver mgntUser mgnt PaymentNotification User API Driver Trip mgnt Microservices Architecture User API Gateway Driver Container User mgnt Container Billing Container Notification Container Payment Container Driver mgnt Container Trip mgnt Microservices Business Intelligence Legacy systems Frontend Storage Compute Security ? Multi-Cloud Hardware OS Libraries App. Bare metal Hardware Hypervisor OS Lib App OS Lib App OS Lib App Virtual Machines Hardware OS Container Mgr Lib App Lib App Lib App Containers Lib App Lib App Lib App Hardware OS Libraries App Mgr App AppApp Serverless (functions) App AppApp App AppApp App AppApp App AppApp Containers / Kubernetes / Serverless Observability in the distributed (and ephemeral) systems/cloud space is non-negotiable Distributed location / responsibilities Distributed systems/code
- 11. © 2018 SPLUNKINC. Customer experience??? SAAS What happens when we stack them? How does this apply to you and your Ops teams? ON PREMISES Legacy systems (Mainframe…) Facilities Dev/PreProd Storage Backup Archive DR Security VMs Containers Micro services AWS (Application 1)Access / Security Database StorageDev Compute Containers App engine GCP (Big Data project 1) Dataflow AWS (Archive) Azure (Application 1) VMs Database VM sets Traffic mger
- 12. © 2018 SPLUNKINC. Customer experience??? SAAS The consequence: only green lights in the war room ON PREMISES Legacy systems (Mainframe…) Facilities Dev/PreProd Storage Backup Archive DR Security VMs Containers Micro services AWS (Application 1)Access / Security Database StorageDev Compute Containers App engine GCP (Big Data project 1) Dataflow AWS (Archive) Azure (Application 1) VMs Database VM sets Traffic mger Cx O BLO SAAS CISO DevSysAdmin MKT ?? ? ? ?
- 13. © 2018 SPLUNKINC. Splunk for IT Operations How do we help with Observability everywhere?
- 14. © 2018 SPLUNKINC. A market leader ITOM IT Operations Management Tools to manage provisioning, capacity, performance and availability of IT OBSERVE ITOA IT operations analytics DECIDE Practice of monitoring systems, and gathering, processing, analyzing & interpreting data from ITOps sources to guide decisions & predict issues AIOps ACCELERATE AIOps platforms enhance IT operations through greater insights by combining big data, machine learning and visualization. SIEM PROTECT security event information management) #1 #2#1 SECURITY IT OPERATIONS Sources: IDC and/or Gartner #2
- 15. © 2018 SPLUNKINC. We reached the limits of the traditional approach Traditional Data Types Not future proof Complex Never Change! Untapped IT-generated machine data (logs, metrics, wired data…) Machine data is messy and unpredictable Requires massive scale You don’t always know which questions to ask 80%
- 16. © 2018 SPLUNKINC. NotconsumablebyhumansConsumablebyhumans Industry Leading Platform For Machine Data Online ServicesNetworks Security Call Detail Records Web Services Telecoms Web Clickstreams Tracing Online Shopping Cart Smartphones and Devices Custom Applications Energy Meters Storage Public Cloud Private Cloud Containers On-Premises Servers GPS Location RFID Packaged ApplicationsDatabases MessagingFirewall Logs Wired DB Mobile IoT APIMetrics DATA Any Amount Any Location Any Source No need to “adapt or structure” the data No database No need to filter data SPLUNKBASE 1600+ Free Apps/add-ons SPLUNK PLATFORM Custom dashboards Report & analyze Monitor and alert Developer Platform Ad hoc search On-prem or cloud PREMIUM APPS “data scientist in a box” IT Ops, DevOps Security Business Analytics, IoT Different people asking different questions on the same data, in real time 3rd Party Phantom Orchestration VictorOps Collaboration CMDB, SNOW… Data lake APM Traces APM Tracing
- 17. © 2018 SPLUNKINC. Structure Machine data = fighting a losing battle
- 18. © 2018 SPLUNKINC. How to find a needle in multiple haystacks? (choose your tool) Network? Database? Middleware? Hardware? Wrong command? Connection? Apache? VM? Mainframe? Load balancer?Wrong code released? Collect ALL data • Collect from all silos • Data in original raw format • Add open sources apps to ingest data on the fly • Schema on the fly • Dynamic thresholding • Realtime correlation Clustering & aggregation • Real time event clustering/correlation • Reduce alert noise • Behavioural analytics • Deduplication Add context • Measure / report on indicators that matters • Add service / business context • Add actionable information to detection Salessso Claims Anomaly detection • Catch issues that thresholds cannot • Reduce event clutter • Deviation from past behaviour • Deviation from peers • Unusual change in features Assisted deep dive investigation • Root cause analysis • Powerful & easy to use search & investigate language ? Predictive Analytics • Predict service health • Predict events • Trend forecasting • Detect influencing entities • Early warning of failure 70% to 90% Reduction in investigation time 15% to 45% Reduction in high priority incidents 67% to 82% Reduction in business impact
- 19. © 2018 SPLUNKINC. UnknownKnown Awareness/DataAvailable Knowns Unknowns Understanding Observability with Splunk Known Knowns (Known problem & solution) Unknown Knowns (didn’t realize but clear solution) Known Unknowns (we see the problem, not the solution) Unknown Unknowns (no idea it’ll happen) Improve the Known- Knowns Dynamic thresholding, automation, schema on fly, real time dashboards… Provide auto correlations, real time search’s, analytics, business process mining… See the Known- Unknowns Discover the Unknown-Knowns Anomaly detection, predictive IT… Ingest any data, ask any question, get answers in real time… Explore the Unknown-Unknowns
- 20. © 2018 SPLUNKINC. Answer new questions, find new unknowns Observe | Monitor | Analyze | Act
- 21. © 2018 SPLUNKINC. It’s a journey Search & Monitor (Any) Data collection Real time monitoring/observability Centralized Machine Data Search Business Insights Business KPIs Insights to drive experienceOperational visibility Service Oriented View Root Cause analysis Stabilize IT Predict & Improve Predict issues Recommend actions based on prior behaviors Increase MTBF
- 22. © 2018 SPLUNKINC.© 2018 SPLUNK INC. Thank you