AppSignal vs Honeycomb: What are the differences?
Developers describe AppSignal as "Monitoring for Ruby and Elixir. By developers, for developers". AppSignal gives you and your team alerts and detailed metrics about your Ruby or Elixir application Sensible pricing, no aggressive sales & support by developers.. On the other hand, Honeycomb is detailed as "Observability for a distributed world--designed for high cardinality data and collaborative problem solving 🐝💖". We built Honeycomb to answer the hard questions that come up when you're trying to operate your software–to debug microservices, serverless, distributed systems, polyglot persistence, containers, and a world of fast, parallel deploys.
AppSignal and Honeycomb can be categorized as "Performance Monitoring" tools.
Some of the features offered by AppSignal are:
- Track errors
- Performance Monitoring
- Compare deploys. Monitor background jobs.
On the other hand, Honeycomb provides the following key features:
- High-performance querying against high-cardinality or sparse events.
- Accepts any structured JSON objects with a write key.
- Submit events via API.
What is AppSignal?
What is Honeycomb?
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Regarding Continuous Integration - we've started with something very easy to set up - CircleCI , but with time we're adding more & more complex pipelines - we use Jenkins to configure & run those. It's much more effort, but at some point we had to pay for the flexibility we expected. Our source code version control is Git (which probably doesn't require a rationale these days) and we keep repos in GitHub - since the very beginning & we never considered moving out. Our primary monitoring these days is in New Relic (Ruby & SPA apps) and AppSignal (Elixir apps) - we're considering unifying it in New Relic , but this will require some improvements in Elixir app observability. For error reporting we use Sentry (a very popular choice in this class) & we collect our distributed logs using Logentries (to avoid semi-manual handling here).
Our primary source of monitoring and alerting is Datadog. We’ve got prebuilt dashboards for every scenario and integration with PagerDuty to manage routing any alerts. We’ve definitely scaled past the point where managing dashboards is easy, but we haven’t had time to invest in using features like Anomaly Detection. We’ve started using Honeycomb for some targeted debugging of complex production issues and we are liking what we’ve seen. We capture any unhandled exceptions with Rollbar and, if we realize one will keep happening, we quickly convert the metrics to point back to Datadog, to keep Rollbar as clean as possible.
We use Segment to consolidate all of our trackers, the most important of which goes to Amplitude to analyze user patterns. However, if we need a more consolidated view, we push all of our data to our own data warehouse running PostgreSQL; this is available for analytics and dashboard creation through Looker.