Remove Availability Remove Comparison Remove Metrics
article thumbnail

Dynatrace extends Synthetic Monitoring capabilities with Network Availability Monitors to validate the availability of infrastructure and services

Dynatrace

As HTTP and browser monitors cover the application level of the ISO /OSI model , successful executions of synthetic tests indicate that availability and performance meet the expected thresholds of your entire technological stack. Our script, available on GitHub , provides details. Overview and detailed requests comparison.

article thumbnail

Migrating Critical Traffic At Scale with No Downtime?—?Part 1

The Netflix TechBlog

The second phase involves migrating the traffic over to the new systems in a manner that mitigates the risk of incidents while continually monitoring and confirming that we are meeting crucial metrics tracked at multiple levels. It provides a good read on the availability and latency ranges under different production conditions.

Traffic 349
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Connect Fluentd logs with Dynatrace traces, metrics, and topology data to enhance Kubernetes observability

Dynatrace

While Fluentd solves the challenges of collecting and normalizing Kubernetes events and logs, Kubernetes performance and availability problems can rarely be solved by investigating logs in isolation. All metrics, traces, and real user data are also surfaced in the context of specific events.

Metrics 191
article thumbnail

Implementing service-level objectives to improve software quality

Dynatrace

By implementing service-level objectives, teams can avoid collecting and checking a huge amount of metrics for each service. According to Google’s SRE handbook , best practices, there are “ Four Golden Signals ” we can convert into four SLOs for services: reliability, latency, availability, and saturation.

Software 276
article thumbnail

Migrating Critical Traffic At Scale with No Downtime?—?Part 2

The Netflix TechBlog

By collecting and analyzing key performance metrics of the service over time, we can assess the impact of the new changes and determine if they meet the availability, latency, and performance requirements. The results are then evaluated using specific metrics to determine whether the hypothesis is valid.

Traffic 287
article thumbnail

HTTP monitors on the latest Dynatrace platform extend insights into the health of your API endpoints and simplify test management

Dynatrace

Thanks to the power of Grail, those details are available for all executions stored for the entire retention period during which synthetic results are kept. It now fully supports not only Network Availability Monitors but also HTTP synthetic monitors. Details of requests sent during each monitor execution are also available.

article thumbnail

Answer-driven release validation with Dynatrace SaaS Cloud Automation

Dynatrace

Service-level indicators (SLIs) are checked against your SLOs early in the lifecycle, including comparison against previous builds. Automated comparison of different timeframes based on SLIs and SLOs. Dynatrace Cloud Automation is currently only available for Dynatrace SaaS deployments. How the evaluation works.

Cloud 245