Observability

Metrics tell you something is wrong. Logs tell you what is wrong. A practical guide on when to use each for effective observability.

Learn how to reduce cloud monitoring overload without dropping critical signals or blowing up observability costs.

A detailed look at observability platforms so you can choose tools that keep visibility high and costs steady as your systems scale.

A quick guide to how seven leading observability tools support full-fidelity telemetry and the architectural choices behind them.

Auto-discovery tools now detect services as they appear and build dashboards instantly. Here are seven platforms that do it well.

Understand observability vs visibility: visibility shows current states, while observability uncovers why systems act the way they do.

Know how asynchronous job monitoring tracks background tasks, ensuring they finish reliably, perform well, and stay visible at scale.

Understand what makes background jobs slow or fail by looking past queue depth to real execution signals.

Service catalog observability tracks discovery, adoption, and runtime accuracy, turning catalogs into measurable infrastructure.

A practical look at common log format standards, how JSON, XML, and key-value logs work, and when to use each in production systems.

Slow Postgres queries killing your app? Learn proven tuning techniques for indexes, VACUUM, connection pooling, and query optimization. Real fixes that cut latency 50-80%.

Application metrics are key performance signals, like latency, error rate, and throughput, that help you understand how your app behaves in production.

Monitor Jaeger in production with core metrics and alerting rules, track trace completion, queue depth, and storage performance at scale.

Diagnose missing Loki metrics by fixing recording rule gaps, remote write failures, and high-cardinality issues in production setups.

Collect metrics with Telegraf without running Prometheus. No scraping, no TSDB tuning, just clean, push-based telemetry to your backend.

Push metrics into Last9 and start tracking Kafka lag, retries, and throughput in real-time.

Visually build, parse, and analyze logs across services, no LogQL required. Get structured insights faster with Query Builder.

Here's how you can build automated log analysis workflows with Last9's Query Logs API

Know how to use Elasticsearch with Python for indexing, searching, and analyzing data, complete with code, tips, and integration examples.

Log loss and cross-entropy are core loss functions for classification tasks, measuring how well predicted probabilities match actual labels.

Centralized logging helps you debug faster, scale smarter, and cut through noise. Here's how to get it right from the start.

Understand how to deploy, scale, and manage Elasticsearch on Kubernetes with the right configs for storage, availability, and performance.

Understand how to monitor your CDN effectively with this easy, practical guide focused on key metrics, common issues, and real-world tips.

Learn which JVM metrics matter, how to track them, and use that data to troubleshoot and improve Java application performance.

Track what matters in Solr. This guide covers key Solr metrics every DevOps and SRE team should monitor to keep search performance sharp.

CloudWatch vs OpenTelemetry: Understand the trade-offs and choose the observability approach that fits your team's architecture and workflows.

Learn how to monitor, troubleshoot, and improve RabbitMQ performance with the right metrics, tools, and observability practices.

Essential techniques for comprehensive SQL Server observability: from setting up monitoring to troubleshooting performance issues and implementing best practices.

Learn how to set up Jaeger for distributed tracing, track requests across services, and troubleshoot issues in modern microservice apps.

Learn how to simplify container observability for your DevOps team by effectively tracking metrics, logs, and traces to improve performance.

Learn the key differences between RUM and synthetic monitoring, and how each approach helps track performance in real-time and preemptively.

API monitoring helps track performance, uptime, and errors. Learn how to build dashboards that give you real-time insights into API health.

Learn how to effectively monitor HBase performance with key metrics, tools, and best practices to ensure your cluster runs smoothly.

Learn the difference between Correlation IDs and Trace IDs, and how they help track requests and diagnose issues in distributed systems.

Learn how traces and spans help you see inside distributed systems—so you can troubleshoot faster and build more reliable software.

Learn how to optimize MySQL queries and identify bottlenecks with a performance analyzer to keep your database running smoothly.

A no-fluff guide to APM observability for DevOps and SREs—tools, tips, and what actually matters when keeping systems healthy.

Observability goes beyond APM—it's not just about metrics, it's about understanding why things break, not just that they did.

Struggling with gaps in your monitoring? Zero code instrumentation fills them by capturing key telemetry without modifying your code.

Learn how to build and optimize observability pipelines with this easy-to-follow guide designed for engineers.

Get clear answers to the most common observability questions—tools, best practices, and strategies for better monitoring.

Get a clear, no-nonsense look at full-stack observability—what it is, why it matters, and how it helps you stay on top of your systems.

Our Dev Evangelist, Prathamesh Sonpatki, shared insights on alert fatigue at a ClickHouse meetup—sparking great conversations on observability.

Learn how to integrate observability into chaos engineering to better understand system behavior and improve resilience during failures.

Learn how a telemetry data platform helps monitor, analyze, and optimize system performance for complex, scalable environments.

Learn the basics of distributed tracing, how it works, and how to implement it for better observability in your microservices architecture.

Learn how Azure Observability empowers you to monitor, optimize, and enhance the performance of your cloud applications and infrastructure.

Single pane of glass monitoring provides a unified view of your system's data, making it easier to track performance and troubleshoot issues.

Learn how data observability helps your business catch issues early, ensuring accurate insights, smarter decisions, and smoother growth.

Learn how unified observability helps you track system health, improve performance, and quickly resolve issues across your environment.

Ready to migrate your observability platform? Here’s what you need to know to make the process smooth and set your team up for success.

Effective Kafka observability is crucial for tracking performance, ensuring reliability, and troubleshooting issues in complex, distributed systems.

eBPF enhances observability by providing deep insights into system performance and security with minimal overhead, ideal for modern, distributed systems.

The Observability Maturity Model helps organizations optimize systems by advancing through stages to improve reliability, performance, and troubleshooting.

Cloud security monitoring is essential to protect data, ensure compliance, and safeguard against growing cyber threats in cloud environments.

DNS monitoring ensures your domain records are accurate, secure, and performing well, helping prevent outages and attacks.

LLM observability is key to ensuring model performance. Learn its importance, best practices, and actionable steps for optimal results and reliability.

Learn the key differences between MongoDB and Elasticsearch, and understand when to use each for your database and search needs.

Learn how to monitor and optimize your GCP resources effortlessly. Simplify performance tracking and keep your services running smoothly.

Fluentd vs Fluent Bit: Discover the key differences, use cases, and how to choose the right tool for your log processing needs.

Boost observability with Fluent Bit and OpenTelemetry! Collect, process, and export logs and metrics easily for smarter monitoring.

Achieve better application performance with full-stack observability, gaining real-time insights to troubleshoot, optimize, and enhance user experience.

Learn how to implement effective Kubernetes observability with metrics, logs, and traces to monitor and optimize your clusters at scale.

Discover the top tracing tools in observability to monitor, analyze, and troubleshoot your systems for better performance and reliability.

Proactive monitoring helps IT teams spot issues early, ensuring smooth operations, minimal disruptions, and a better user experience.

OpenSearch and Elasticsearch are both powerful search engines, but OpenSearch offers an open-source alternative with community-driven development.

Golden Signals—latency, traffic, error rate, and saturation—help SRE teams monitor system health and avoid costly performance issues.

Last9’s Telemetry Warehouse now supports Logs and Traces, offering a unified view for high cardinality observability to simplify monitoring and troubleshooting.

Check out these straightforward tips to manage your metrics and logs better. You can keep your monitoring effective while cutting down on costs!

Learn everything about Application Performance Monitoring (APM), from its definition to its crucial role in optimizing application performance.

What are the alternatives to Prometheus? A guide to comparing different Prometheus Alternatives.

Explore Prometheus Remote Write: scale your monitoring effortlessly. Learn how it works, its benefits, and top tips for cloud-native setups.

We break down the essentials of streaming aggregation and its impact on modern data processing.

This guide provides an in-depth look at its setup and usage, helping you monitor and manage your Kubernetes clusters more efficiently.

Get a detailed look at the top cloud monitoring tools of 2024. Compare leading solutions to understand their features and performance, helping you choose the best fit for your cloud infrastructure.

Practical tips for monitoring, analyzing, and improving system performance.

The guide discusses the essential components, challenges, popular tools, and advanced techniques that define effective log aggregation.

This article explores OpenTelemetry vs. traditional APM tools, comparing their strengths, weaknesses, and use cases to help you choose wisely.

This article breaks down the fundamentals, from data collection to analysis, to help you gain deeper insights into your applications.

Observability is the continuous analysis of operational data, telemetry is the operational data that feeds into that analysis, and monitoring is like a radar for your system observing everything about your system and alerting when necessary.

The software monitoring world is broken because of a TSDB. We deserve a TSDW

The OpenTelemetry Collector simplifies data collection, processing, and export for metrics, logs, and traces. Learn about its architecture, deployment, and examples.

A wishlist of things that need to change in the world of software monitoring

Chasing shiny new toys, as always ;)

If you want to bring down your monitoring costs, you need to shake up a decision paralysis in engineering

Observability is often a misunderstood and misused term.  It has come to mean nothing and everything at this point. Read more on how Observability can be viewed from the lens of a Radar and a Black Box.

We're in a peak tech winter. What should engineering teams focus on when product velocity dwindles?

What does the Rasmussen model teach us about Site Reliability Engineering?

Using 'Sharding' to tame High Cardinality data for Levitate - Our Time Series Data Warehouse

If all companies are software companies, all companies need better Observability to understand how performative their software is

Recap of QCon New York 2023 Conference

Engineering organizations that ship fast have Observability as part of their core DNA.

Understanding Metrics, Logs, Events and Traces - the key pillars of observability and their pros and cons for SRE and DevOps teams.

What's the difference between SREs and Platform Engineers? How do they differ in their daily tasks?

Comparison between Prometheus and Datadog - two of the most popular monitoring tools in the market today

What's the difference between SREs and DevOps professionals? How do they differ in their daily tasks?

Whoever owns Reliability should define its parameters. But who owns the Reliability of a Product? Engineering? Product Management? Or the Customer success team?

From Robocars to Reliability — SRE with self-driving cars; mapping out where the Observability space is in conjunction with self-driving cars

The Reliability industry needs a managed, non-vendor lock-in answer to spiraling costs, high cardinality and the toil of managing a tsdb

SRECon is a conference hosted by USENIX and is focused on site reliability, distributed systems, and systems engineering at scale. A Recap of SRECon Americas 2023.

How does a DevOps/Site Reliability Engineer plan for "Cricket scale"? How do you warm systems' about to witness 30+ million concurrent users?

Explaining Reliability Engineering to a 5-year-old.

From the trenches at Games24x7 — Sanjay, on how Reliability engineering should drive core business metrics

A recap of the talks from the Observability and Monitoring dev room at Fosdem 2023.

No tool can magically offer you 99.999s. Observability is largely about the basics. And basics are boring. But, boring is hard. Boring is battle tested.

Managing time series databases is hard. We've evolved to services, yet monitoring lags. Our solution powers critical workloads at a lower cost.

This article will go over what Prometheus exporters are, how to properly find and utilize prebuilt exporters, and tips, examples, and considerations when building your own exporters.

In reliability engineering, three concepts keep getting talked about - DevOps, SRE and Platform Engineering. How do they differ?

Deep dive into how to improve the performance of Prometheus Remote Write at Scale based on real-life experiences

How does one ‘detect change’ in a complex infrastructure, so you don’t lose out on critical revenues — A short SRE story

A key challenge is aligning engineering health metrics with business goals. How can business measure engineering, and engineering show its value?

When dealing with Time Series databases, I always got confused with Sample vs Metrics vs Cardinality. Here’s an explanation as I have understood it.

A comparison of all the popular time series databases. Prometheus, Influx, M3Db, Levitate.

In the early days of Google, a lot of users were asking for 30 results on the first page of search results. So after long deliberation, Marissa Mayer, then the Product Manager for google.com, decided to run the A/B test for ten vs 30 results. When the results came in, they were in for a surprise.

Exciting news! We've secured an $11M Series A funding round led by Sequoia Capital India to fuel our growth and innovation at Last9!

Understanding how to measure the health of your servcie, benefits of using SLOs, how to set compliances and much more...

Service Level Objectives (SLOs) dominate the software industry, but where did they come from?

A well-thought-out approach to SRE, which will help site reliability engineers and software engineers develop and maintain a useful, consistent, and effective SRE strategy for their products!

You can either love running or hate running, but you will definitely love this analogy - take a fresh look at SLOs!

How do you set latency-based alerts? A common approach is 95% of requests completed in 350ms, but is it really that simple?

Gone are the days of yore when we named are our servers Etsy, Betsy, and Momo, fed them fish, and cleaned their poop.