OpsMatters’ Post

Datadog is streamlining DevSecOps workflows with new tools and capabilities, including integration with OpenTelemetry and enhancements to its On-Call tool. As Mike Vizard reports, these updates optimize incident management by maintaining context with observability data. #Datadog #DevSecOps #OpenTelemetry #Observability #IncidentManagement https://lnkd.in/gPX2Ksrz

Do you have a need to have all your metadata in one place? Then Datadog is worth checking out. It’s a leading observability tool that provides comprehensive monitoring across applications, infrastructure, and services. It integrates metrics, traces, and logs into a unified platform, enabling real-time insights into system performance. Key features include synchronised dashboards for visualising data from multiple sources and machine learning capabilities for automatic anomaly detection, which helps prevent downtime. Datadog facilitates seamless data collection and analysis, and helps with reconciliation of data across systems in real-time. Its user-friendly interface simplifies navigation and reporting, allowing teams to focus on critical tasks. https://www.datadoghq.com/

Have you experienced unforeseen metric and log data volume spikes leading to cost overages with Datadog (or related Observability tools)? These tools are great and really helpful. However, Enterprises have become frustrated with data spikes and storing data they do not use. Mezmo has a powerful set of capabilities which dynamically protects against data volume spikes, notifying application teams and protecting cost overruns. How? Mezmo captures metric and log data streams at the point of ingest through processors and monitors to dynamically trim, sample, dump data before they are stored in your particular O11Y tools. This also provides your business the ability to profile your data for insights, make smart optimization decisions and action in new ways proactively. My colleague Braxton Johnston created a product walkthrough showing one example of how Mezmo protects large data volumes spikes.  Here is the demo: https://lnkd.in/euaksZhM

How do you monitor the performance of backend applications? To monitor the performance of backend applications, we can use the following approaches and tools: • APM Tools: New Relic, Dynatrace, AppDynamics • Logging: ELK Stack, Graylog, Splunk • Metrics and Monitoring: Prometheus, Grafana, Datadog • Distributed Tracing: Jaeger, Zipkin • Health Checks and Alerts: Prometheus Alertmanager, PagerDuty, Opsgenie • Synthetic Monitoring: Pingdom, UptimeRobot • Error Tracking: Sentry, Rollbar • Performance Profiling: Pyroscope, Flamegraphs #softwareengineering #backend

#SLI: the metric that measures reliability from the service consumers' perspective #SLO: the commitment from service provider to the consumer But how do we know where are we in terms of those commitments on a given day? The answer is service level status or #SLS for short. Read the story of why I coined this term as well as examples and illustrations. SLS is a key concept to put failures in perspective and tie alerting to SLO. #sre #serviceDesign #serviceLevels #metrics #observability Nobl9 Datadog Grafana Labs

Protect Critical Data by Location using Dynamic Attributes with NextLabs CloudAz Dynamic Attribute Provider This allows division managers to access all resources within their regions. This enables the NextLabs policy controller to fetch attributes dynamically from sources like Databases, CSV, Rest APIs and many other sources during policy evaluation. #nextlabs #dynamicattributes https://lnkd.in/eagg4S3W

Our Signals migrator from PagerDuty, OpsGenie, and Splunk On-Call is released. And it's open source. https://lnkd.in/etVccGNU Here's what it comes with: 1. It's an interactive CLI that connects to your alerting provider and walks you through mapping your alerting tool to Signals 2. It exports Terraform code so you not only migrate to a modern alternative, you get it as infrastructure as code. 3. For PagerDuty, we've made it so you can map your services in PD as teams in FireHydrant (or if it really is a service, import it into your catalog) 4. Escalation policies, schedules, etc, are all exported as FireHydrant Signals resources There's also a nice Datadog migration script to update your monitors to then point at FireHydrant's Signal endpoints. Signals is an amazing on-call experience, and this tool makes it so much easier to start using it.

Datadog Observability Pipelines enables you to cost-effectively collect, transform, and route logs from any source to any destination at a petabyte scale. Take full control of your observability data by making value-based decisions in your own infrastructure to optimize volume, flexibly route data, stay compliant, and standardize data. Datadog Observability pipelines enables teams to: Control costs, improve visibility Simplify migrations, reduce lock-in Protect sensitive data Enforce data quality Monitor and manage pipelines through a single control plane https://lnkd.in/eVMHQFxU

🚀 Are you searching for a powerful monitoring solution? Look no further than MetricFire! With real-time visibility, easy setup, and unmatched scalability, MetricFire empowers you to stay ahead of potential issues in your infrastructure. Smart alerts and seamless integration keep your systems running smoothly. Discover how MetricFire can transform your monitoring experience today! https://lnkd.in/gmjJPn76 #Monitoring #DevOps #MetricFire

The latest update for #SigNoz includes "#OpenTelemetry vs Datadog - Choosing the Right #Monitoring Tool" and "Kibana vs. Grafana - A Scenario-Based Decision Guide