Dynatrace

NOVEMBER 16, 2021

Dynatrace has recently extended its Kubernetes operator by adding a new feature, the Prometheus OpenMetrics Ingest , which enables you to import Prometheus metrics in Dynatrace and build SLO and anomaly detection dashboards with Prometheus data. Here we’ll explore how to collect Prometheus metrics and what you can achieve with them.

Metrics 210

Metrics Infrastructure Open Source Database 210

Dynatrace

OCTOBER 7, 2020

Dynatrace recently opened up the enterprise-grade functionalities of Dynatrace OneAgent to all the data needed for observability, including metrics, events, logs, traces, and topology data. Davis topology-aware anomaly detection and alerting for your custom metrics. Topology and non-topology metrics—what’s the difference?

Metrics 246

Metrics Analytics Storage Monitoring 246

Dynatrace

DECEMBER 9, 2020

If you’re running SAP, you’re likely already familiar with the HANA relational database management system. However, if you’re an operations engineer who’s been tasked with migrating to HANA from a legacy database system, you’ll need to get up to speed quickly. Avoid false positives with auto-adaptive baselining.

Infrastructure 209

Infrastructure Database Monitoring Metrics 209

Dynatrace

NOVEMBER 1, 2021

As cloud applications have become the norm, the databases that power these applications are now typically run as managed services by cloud providers. Optimizing cloud services can prove quite challenging because logs, metrics, and traces are not always put together in context, and you don’t have access to the underlying hosts.

Azure 205

Azure Database Performance Monitoring 205

Dynatrace

MAY 28, 2024

What about correlated trace data, host metrics, real-time vulnerability scanning results, or log messages captured just before an incident occurs? Depending on which app is in use, one glance at a histogram provides invaluable insight into managing clouds, databases, Kubernetes environments, and infrastructure.

Analytics 178

Analytics Infrastructure Database Monitoring 178

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.

Open Source 227

Open Source Metrics Cloud Transportation 227

Dynatrace

MARCH 29, 2024

This year, Google’s event will take place from April 9 to 11 in Las Vegas. Visit Dynatrace booth #1141 during the event to explore how its real-time insights and optimization capabilities ensure seamless scalability and performance. Learn more.

Google 270

Google Innovation Cloud Analytics 270

Dynatrace

NOVEMBER 27, 2020

Welcome back to the second part of our blog series on how easy it is to get enterprise-grade observability at scale in Dynatrace for your OpenTelemetry custom metrics. In Part 1 , we announced our new OpenTelemetry custom-metric exporters that provide the broadest language coverage on the market, including Go , .NET record(value); }.

Metrics 143

Metrics Open Source Lambda Serverless 143

The Netflix TechBlog

APRIL 27, 2023

Ruchir Jha , Brian Harrington , Yingwu Zhao TL;DR Streaming alert evaluation scales much better than the traditional approach of polling time-series databases. It allows us to overcome high dimensionality/cardinality limitations of the time-series database. It opens doors to support more exciting use-cases.

Storage 288

Storage Cache Metrics Database 288

Dynatrace

MARCH 6, 2024

It also includes various built-in software components for database management, security, and application development. It then collects performance data using existing database services running on your system. Gaining knowledge about IBM i performance can be a challenging and pricey task. Nothing is installed on your IBM i systems.

Monitoring 243

Monitoring Infrastructure Metrics Analytics 243

Dynatrace

AUGUST 12, 2019

With OneAgent installed on an application server, Davis, the Dynatrace AI causation engine, continuously analyzes all database statements within the context of your applications. Now, with Oracle database insights, we’re going even deeper, giving you visibility into what’s going on in the database layer.

Database 128

Database Metrics Cache Servers 128

Percona

JUNE 22, 2023

To make data count and to ensure cloud computing is unabated, companies and organizations must have highly available databases. A basic high availability database system provides failover (preferably automatic) from a primary database node to redundant nodes within a cluster. HA is sometimes confused with “fault tolerance.”

Availability 108

Availability Database Open Source Hardware 108

Dynatrace

FEBRUARY 28, 2024

Challenges to exploratory data analytics Among the challenges analysts face are multiple heterogeneous data sources, noisy or incomplete data, insufficient causal reasoning (faulty connections between event cause and effect), and untrustworthy AI , according to an article from the Columbia University Data Science Institute.

Analytics 219

Analytics Metrics Media Monitoring 219

Percona

AUGUST 30, 2023

Data powers everything, and unlike coal and coal combustion, data and databases aren’t going away. Any organization that uses personal and other sensitive data must have a firm, proven plan for business continuity in the event of a disaster or cyberattack. It’s suitable for databases with moderate change rates.

Database 88

Database Hardware Open Source Strategy 88

Dynatrace

FEBRUARY 1, 2024

But organizations must also be aware of the pitfalls of AI: security and compliance risks, biases, misinformation, and lack of insight into critical metrics (including availability, code development, infrastructure, databases, and more). In this example, there is a suspicious increase in scripting events.

Artificial Intelligence 195

Artificial Intelligence Analytics Efficiency Database 195

Dynatrace

FEBRUARY 1, 2024

Any problem, such as a simple software update overburdening a critical database, can cause a ripple effect that degrades the performance of dependent services or applications. For example, an unnoticed database strain could slow down the response time of a web frontend, resulting in poor user experience.

Infrastructure 190

Infrastructure Metrics Network Monitoring 190

SQL Performance

APRIL 15, 2020

SQL Server has always provided the ability to capture actual queries in an easily-consumable rowset format – first with legacy SQL Server Profiler, later via Extended Events, and now with a combination of those two concepts in Azure SQL Database. Legacy Profiler "Standard" trace events.

Azure 96

Azure Database Tuning Network 96

HammerDB

NOVEMBER 22, 2021

Introducing the PostgreSQL performance metrics viewer. HammerDB included a graphical performance metrics view for the Oracle database only. HammerDB includes the same functionality for PostgreSQL enabling the user to drill down on database metrics in real time. PostgreSQL Graphical Metrics. postgresql-14.1/contrib/pg_stat_statements$

Metrics 62

Metrics Benchmarking C++ Database 62

The Netflix TechBlog

MARCH 10, 2023

Production Use Cases Real-Time APIs (backed by the Cassandra database) for asset metadata access don’t fit analytics use cases by data science or machine learning teams. After reading the asset ids using one of the ways, an event is created per asset id to be processed synchronously or asynchronously based on the use case.

Media 237

Media Traffic Processing Design 237

Dynatrace

AUGUST 9, 2023

With up to 70% of security events going uninvestigated, security analysts need all the help they can get. After a security event, many organizations often don’t know for months (or even years) when why or how it happened. Teams must evolve to continuously create reliable, automated responses based on precise data-driven insights.

Analytics 226

Analytics Metrics Database Storage 226

Dynatrace

FEBRUARY 16, 2023

The short answer: The three pillars of observability—logs, metrics, and traces—converging on a data lakehouse. This unified approach enables Grail to vault past the limitations of traditional databases. And without the encumbrances of traditional databases, Grail performs fast. “In

Analytics 195

Analytics Innovation Metrics Database 195

Dynatrace

JANUARY 31, 2024

The RAG process begins by summarizing and converting user prompts into queries that are sent to a search platform that uses semantic similarities to find relevant data in vector databases, semantic caches, or other online data sources.

Cache 212

Cache Azure Infrastructure Monitoring 212

Dynatrace

MAY 17, 2023

Making applications observable—relying on metrics, logs, and traces to understand what software is doing and how it’s performing—has become increasingly important as workloads are shifting to multicloud environments. We also introduced our demo app and explained how to define the metrics and traces it uses.

Metrics 179

Metrics Monitoring Database Network 179

HammerDB

OCTOBER 23, 2023

HammerDB uses stored procedures to achieve maximum throughput when benchmarking your database. However, there can be a lack of understanding of the benefits that stored procedures bring or if you have a benchmarking tool or database that doesn’t support stored procedures, then you have nothing to compare against.

Benchmarking 62

Benchmarking Database Network C++ 62

Dynatrace

MARCH 20, 2024

External dependencies Many applications rely on external services, such as databases, APIs, or third-party services. Changes in application code or configurations can impact performance metrics, affecting user experience and application functionality. Consider a scenario where a web application depends on an external payment gateway.

Open Source 276

Open Source Hardware DevOps Infrastructure 276

Dynatrace

DECEMBER 9, 2020

Most applications communicate with databases to, for example, pull a catalog entry or submit a new record when an order is placed. To achieve this, there must be a healthy connection between the application and the database. Application servers use connection pools to maintain connections with the databases that they communicate with.

Traffic 140

Traffic Performance Database Metrics 140

Dynatrace

NOVEMBER 3, 2021

Monitoring focuses on watching specific metrics. Observability is the ability to understand a system’s internal state by analyzing the data it generates, such as logs, metrics, and traces. For example, we can actively watch a single metric for changes that indicate a problem — this is monitoring.

Monitoring 229

Monitoring Metrics DevOps Scalability 229

Dynatrace

FEBRUARY 8, 2021

Every service and component exposes observability data (metrics, logs, and traces) that contains crucial information to drive digital businesses. Logs and events play an essential role in this mix; they include critical information which can’t be found anywhere else, like details on transactions, processes, users and environment changes.

Cloud 262

Cloud Azure Analytics AWS 262

Dynatrace

APRIL 20, 2023

Logs are automatically produced and time-stamped documentation of events relevant to cloud architectures. ” Weighing the value and cost of indexed databases vs. Grail With standard index databases, teams must choose relevant indexes before data ingestion. Grail enables 100% precision insights into all stored data.

Analytics 196

Analytics Infrastructure Storage Efficiency 196

Dynatrace

JANUARY 31, 2024

Scenario : For many B2B SaaS companies, the number of reported customers is an important metric. In this scenario, a manually triggered run of a production pipeline had the unintended consequence of duplicating the reported customer metric.

DevOps 200

DevOps Analytics Airlines Metrics 200

Dynatrace

OCTOBER 4, 2022

Achieving the ideal state with aggregated, centralized log data, metrics, traces , and other metadata is challenging—particularly for multicloud environments. They can call on dozens of databases and deliver gigabytes of data across myriad devices. Metrics are often tracked and measured relative to a baseline or threshold.

Analytics 230

Analytics Storage Infrastructure Metrics 230

Dynatrace

OCTOBER 4, 2022

The only way to address these challenges is through observability data — logs, metrics, and traces. This purpose-built data lakehouse approach for observability, security, and AIOps offers schema-less ingestion of various data types, including logs, metrics, traces, user data, business data, and topology data. Event severity.

Analytics 200

Analytics Software Software Storage 200

Dynatrace

APRIL 21, 2022

You can create custom log metrics for smarter and faster troubleshooting, and you will be able to understand log data in the context of your full stack, including real user impacts. The default values cover a large range of different cluster sizes; you can modify them according to your needs, based on the ActiveGate self-monitoring metrics.

Azure 224

Azure Metrics AWS Monitoring 224

Dynatrace

OCTOBER 22, 2021

We are changing the pricing for Log Monitoring v2, now ingested log events consume DDU. Removed deprecated endpoints /metrics/series and /metrics/descriptors in favor of /metrics/query and /metrics. Metric and configuration storage database was updated to Cassandra 3.11.11

Metrics 222

Metrics Monitoring Storage Database 222

Dynatrace

DECEMBER 2, 2021

Symptoms : No data is provided for affected metrics on dashboards, alerts, and custom device pages populated by the affected extension metrics. Removed seven-day preview from create/edit custom event for alerting pages. Settings > Anomaly detection > Database services. Extension logs display errors.

Lambda 203

Lambda Azure Metrics Monitoring 203

The Netflix TechBlog

AUGUST 1, 2022

As the system evolves to solve more and more use cases, we have expanded its scope to handle not only the CDC use cases but also more general data movement and processing use cases such that: Events can be sourced from more generic applications (not only databases). A pipeline can be created from the UI or via our declarative API.

Processing 272

Processing Transportation Entertainment Tuning 272

Dynatrace

JANUARY 16, 2023

The strongest Kubernetes growth areas are security, databases, and CI/CD technologies. Strongest Kubernetes growth areas are security, databases, and CI/CD technologies. Of the organizations in the Kubernetes survey, 71% run databases and caches in Kubernetes, representing a +48% year-over-year increase. Java, Go, and Node.js

Open Source 349

Open Source Java Operating System Programming 349