Observability & DevOps Glossary
Plain-language definitions of the monitoring, observability and security terms engineering teams use every day.
AIOps
AIOps (artificial intelligence for IT operations) applies machine learning and analytics to monitoring data, such as metrics, logs, traces and events, to cut alert noise, group related signals and point teams to the likely cause of a problem.
AWS Monitoring
AWS monitoring is the practice of collecting and analyzing metrics, logs and traces from Amazon Web Services resources, such as EC2, RDS, Lambda and load balancers, and from the applications running on them, to keep them available, fast and cost-efficient.
Cloud Performance Management
Cloud performance management is the practice of measuring and improving how applications and infrastructure perform in the cloud: tracking response time, errors, availability, resource usage and cost, so services stay fast without overspending.
Container
A container is a lightweight, standalone package that bundles an application with its libraries, runtime and configuration, and runs it as an isolated process that shares the host operating system’s kernel.
Continuous Monitoring
Continuous monitoring is the automated, ongoing collection and analysis of data from applications, infrastructure, networks and security controls, so teams catch performance problems, failures and threats as they happen instead of in periodic reviews.
DevOps
DevOps is a set of practices and a culture that brings software development and IT operations together, so teams can ship changes often and reliably through automation, shared ownership and fast feedback from production.
Incident Management
Incident management is the process teams use to detect, respond to, resolve and learn from unplanned disruptions to a service, such as outages, errors or slowdowns, so normal service is restored quickly and with the least impact on users.
Incident Response
Incident response is the structured set of steps a team follows when something goes wrong, such as a security breach, an outage or a data leak, to contain the damage, remove the cause, restore normal operations and prevent a repeat.
Kubernetes
Kubernetes (K8s) is an open-source platform that automates deploying, scaling and running containerized applications across a cluster of machines. Google open-sourced it in 2014, and the Cloud Native Computing Foundation (CNCF) now maintains it.
Load Balancer
A load balancer is a device or service that distributes incoming network traffic across several servers, so no single server is overwhelmed, and that stops sending requests to servers that fail health checks.
Log Analysis
Log analysis is the process of collecting, parsing, searching and interpreting log data from applications, servers and devices, to troubleshoot problems, understand system behavior, investigate security events and meet compliance requirements.
Log File
A log file is a file that records events, in time order, as they happen in an operating system, application, server or device, such as requests, errors, warnings, logins and configuration changes.
Microservices
Microservices is an architectural style in which an application is built as a set of small, independently deployable services, each owning one business capability and its own data, that communicate over APIs or messaging.
Network Performance Management (NPM)
Network performance management (NPM) is the practice of measuring, analyzing and improving how well a network delivers traffic, tracking availability, bandwidth, latency, packet loss and jitter across devices, links and paths, so applications and users get a reliable connection.
Network Traffic Analysis
Network traffic analysis (NTA) is the process of capturing and inspecting network traffic, as flow records or full packets, to understand what is moving across a network, troubleshoot performance and detect suspicious or malicious activity.
Prometheus Monitoring
Prometheus is an open-source monitoring system and time-series database that collects metrics by scraping HTTP endpoints, stores them with labels, and lets you query and alert on them with its query language, PromQL.
Real-Time Dashboard
A real-time dashboard is a visual display that updates continuously with live data, such as request rates, error counts, latency and resource usage, so teams can see the current state of a system at a glance and react as things change.
Root Cause Analysis
Root cause analysis (RCA) is a structured method for finding the underlying reason a problem happened, not just its symptoms, so that the fix stops it from happening again.
SaaS Monitoring
SaaS monitoring is the tracking of availability, performance and errors in software-as-a-service applications: both the SaaS product you run for customers and the third-party SaaS tools and APIs your business depends on.
Server Monitoring
Server monitoring is the continuous tracking of a server’s availability, resource usage and running services, including CPU, memory, disk, network and processes, so problems are found and fixed before they affect the applications and users that depend on it.
Serverless
Serverless is a cloud computing model in which the provider runs and scales the servers for you: you deploy code or use managed services, pay only for what you use, and capacity scales automatically, including down to zero.
SIEM
SIEM (security information and event management) is software that collects log and event data from across an organization’s systems, normalizes and correlates it, and alerts security teams to threats, while keeping a searchable record for investigations and compliance.
Storage Monitoring
Storage monitoring is the tracking of capacity, performance and health across storage systems, such as local disks, SAN and NAS arrays, cloud volumes and object storage, so applications don’t slow down or fail because a disk is full, slow or failing.
Synthetic Transaction Monitoring
Synthetic transaction monitoring runs scripted actions, such as logging in, searching or placing an order, against an application on a schedule and from different locations, to check that critical journeys work and measure how fast they are, even when no real users are active.