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Here are some stack decisions, common use cases and reviews by companies and developers who chose Datadog in their tech stack.
Need advice on this.
Which one should I use for logging and error monitoring ( Datadog / Sentry / Stackdriver )?
Open to any other solutions.
We wanted to have a tool that has both APM and error monitoring stuff included in one.
I preferred to go to New Relic as the free version offers 100gb storage but have seen some "not good" comments about it compared to Datadog.
My teammates suggested AppSignal.
So which one should be a good option to give a try?
Tech Stach -> Ruby on Rails, Rails-react, Amazon EC2 machine.
Hello :) We are using Datadog on Kong to monitor the metrics and analytics.
We feel that the cost associated with Datadog is high in terms of custom metrics and indexations. So, we planned to find an alternative for Datadog and we are looking into Grafana implementation with kong.
Will the shift from Datadog to Grafana be a wise move and flawless?
We are evaluating an APM tool and would like to select between AppDynamics or Datadog. Our applications are largely hosted on Microsoft Azure but we would keep the option to move to AWS or Google Cloud Platform in the future.
In addition to core Azure services, we will be hosting other components - including MongoDB, Keycloak, PagerDuty, etc. Our applications are largely C# and React-based using frontend for Backend patterns and Azure API gateway. In addition, there are close to 50+ external services integrated using both REST and SOAP.
Looking for the most straightforward APM tool to use with a Python CRUD stack. We would like to have flame graphs of individual transactions. We'd also like to see SRE tools for monitoring, alerting, and incident response. We are leaning towards Datadog. Thoughts?
I'm considering moving from Flask to Quart, does anyone have some experience with this migration?
I expect possible problems with connexion which we use as OpenAPI specification.
Would be good if someone can point downsides of moving to the Quart framework so I can double-check if my plan is worth doing.
Other libs and tools used in the project: SQLAlchemy, alembic, PostgreSQL, Datadog
cons for now:
- Refactoring uncertainty (not sure how big of a task is it)
- Connexion might not work with Quart (moving to another library)
- ...
Blog Posts
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+44Datadog's Features
- 14-day Free Trial for an unlimited number of hosts
- 200+ turn-key integrations for data aggregation
- Clean graphs of StatsD and other integrations
- Slice and dice graphs and alerts by tags, roles, and more
- Easy-to-use search for hosts, metrics, and tags
- Alert notifications via e-mail and PagerDuty
- Receive alerts on any metric, for a single host or an entire cluster
- Full API access in more than 15 languages
- Overlay metrics and events across disparate sources
- Out-of-the-box and customizable monitoring dashboards
- Easy way to compute rates, ratios, averages, or integrals
- Sampling intervals of 10 seconds
- Mute all alerts with 1 click during upgrades and maintenance
- Tools for team collaboration
