Why Open Source Is Important: Accesibility to Innovation for Everyone
Valkey OSS Developer Advocate Roberto Luna Rojas shares why open source matters to him - and the world.
Operations | Monitoring | ITSM | DevOps | Cloud
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The latest News and Information on Observabilty for complex systems and related technologies.
APM vs Observability: Observing beyond APM
In my previous post I made a bold, sweeping statement that APM is not - in the most specific sense - a subset of observability. Still standing by it I stand by that because words matter and - like many "monitoring engineers" (IT folks who make monitoring and observability their specialty) - I, too, bear scars from the flame-wars on Twitter back in the 2020's where we fought internecine battles over the proper definition of (and number of pillars in) “observability”.
Introducing Honeycomb Intelligence Canvas
Canvas is an AI-guided workspace inside Honeycomb that combines an AI assistant with an interactive notebook for visualizing query results and traces. You can ask a natural language question about your data and Canvas will immediately start exploring your traces, through multiple queries and other tools, to find the right next steps. Instead of having to write each query yourself, Canvas automatically proposes relational queries, comparisons, and visualizations that explain why an SLO fired or what changed after a deploy.
Pastries with SREs: Limitless observability and uncompromised donuts
In this episode of Pastries with SREs, we dig into Limitless Observability with a sweet side of unified observability strategy. If you're tired of siloed tools, fractured data, and swivel-chair investigations, this one’s for you. We explore: Why are silos still the norm in modern observability? What’s the true cost of inefficiencies across logs, metrics, and traces? How can SREs, IT operations, and dev teams shift to a no-compromise, unified observability model?
Meet Canvas: Your AI-guided Workspace Within Honeycomb
Modern systems are wonderfully capable, but relentlessly complex. Debugging across microservices, frontends, and cloud edges often means switching between five or more tools, trying to stitch together “what changed” and “why it broke.” Honeycomb’s wide events model has proven to be a superpower for taming that complexity, by allowing you to easily observe and query end-to-end traces without worrying about how much granular data you attach to your events.
Full-Stack Observability with VictoriaMetrics in the OTel Demo
The OpenTelemetry Astronomy Shop is a widely used demonstration environment designed to illustrate the concepts and practical implementation of observability in distributed systems. Built as a microservice-based e-commerce application, the demo provides developers with a near real-world environment where they can explore how telemetry data—metrics, logs, and traces—can be collected, processed, and visualized.
Introducing Anomaly Detection: Your Early Warning System for Service Health
Modern engineering teams face a persistent challenge: knowing when something goes wrong before their customers do. With microservices architectures sprawling across dozens or hundreds of services, creating comprehensive alerting becomes an overwhelming task. You're left playing whack-a-mole with manual alert configurations, often missing critical issues or drowning in false positives.
Visually identify observability gaps with Cloudcraft in Datadog
Modern cloud environments are highly complex and dynamic, with critical services relying on large numbers of ephemeral resources. Ensuring observability coverage across this landscape is essential for troubleshooting, maintaining reliability, optimizing performance, and enforcing security standards. But as environments grow more elaborate and their ownership more dispersed, tracking observability coverage becomes increasingly challenging.
Visualize Logs Alongside Metrics: Complete Observability Elasticsearch Performance
Elasticsearch is a distributed search and analytics engine that powers everything from log management platforms to e-commerce search bars. It excels at indexing and retrieving large volumes of data quickly, but like any complex system it can slow down under heavy load or inefficient queries.
Introducing Honeycomb Intelligence Anomaly Detection
Modern teams face a persistent challenge: knowing when something goes wrong before their customers do. With architectures sprawling across dozens or hundreds of services, creating comprehensive alerting becomes an overwhelming task. You're left playing whack-a-mole with manual alert configurations, often missing critical issues or drowning in false positives. Today, we're excited to announce our solution to this challenge: Anomaly Detection (currently in alpha), Honeycomb's proactive approach to understanding and acting on service health.