2019 Blog Innovation Metrics 
Dynatrace
OCTOBER 15, 2021
Loosely defined, observability is the ability to understand what’s happening inside a system from the knowledge of the external data it produces, which are usually logs, metrics, and traces. Logs, metrics, and traces make up the bulk of all telemetry data. The data life cycle has multiple steps from start to finish.
Dynatrace
APRIL 15, 2022
But modern cloud infrastructure is large, complex, and dynamic — and over time, this cloud complexity can impede innovation. “Second, we wanted to improve our rollout of the DevSecOps capability, as well as improve our agility and our ability to innovate faster.” “We have a rich metric expression language.
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Dynatrace
SEPTEMBER 2, 2020
With an always-updated, high-fidelity view of how everything interoperates, Dynatrace facilitates continuous automation—deployment, configuration, updates, upgrades—so instead of wasting time doing manual, repetitive tasks, BizDevOps teams can focus on innovative, high-value tasks that drive better business outcomes.
Dynatrace
MAY 26, 2021
This blog dives into what we learned by listening to experts in the field and the key takeaways we gathered from the talks. To improve their alerting system, the team decided to move to SLO/SLI-based alerting, which require deeper knowledge of the application but are more helpful than generalized metric alerts. We second that.
Dynatrace
JULY 31, 2020
Loosely defined, Observability boils down to inferring the internal health and state of a system by looking at the external data it produces, which most commonly are logs, metrics, and traces. The answer is in the data collection, and more specifically, how the logs, metrics, traces are collected. What are the plans for the future?
Dynatrace
MAY 26, 2021
This blog dives into what we learned by listening to experts in the field and the key takeaways we gathered from the talks. To improve their alerting system, the team decided to move to SLO/SLI-based alerting, which require deeper knowledge of the application but are more helpful than generalized metric alerts. We second that.
Dynatrace
JULY 31, 2020
Loosely defined, Observability boils down to inferring the internal health and state of a system by looking at the external data it produces, which most commonly are logs, metrics, and traces. The answer is in the data collection, and more specifically, how the logs, metrics, traces are collected.
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