Dynatrace

MARCH 6, 2024

It is based on the IBM AS/400 system and is known for its reliability, scalability, and security features. 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.

Monitoring 231

Monitoring Infrastructure Metrics Analytics 231

Dynatrace

MARCH 29, 2023

AlloyDB is a fully managed, PostgreSQL-compatible database service for highly demanding enterprise database workloads. Through our partnership, customers can utilize Dynatrace alongside AlloyDB to gain more visibility and insights into data stored across databases and locations, including in AlloyDB.”

Google 216

Google Metrics Cloud Analytics 216

Scalegrid

DECEMBER 21, 2023

Redis® Monitoring Essentials Ensuring the performance, reliability, and safety of a Redis® database requires active monitoring. With these essential support systems in place, you can effectively monitor your databases with up-to-date data about their health and functioning status at all times.

Strategy 130

Strategy Monitoring Latency DevOps 130

Dynatrace

JUNE 9, 2023

They’re unleashing the power of cloud-based analytics on large data sets to unlock the insights they and the business need to make smarter decisions. From a technical perspective, however, cloud-based analytics can be challenging. The sheer number of permutations can break traditional databases.

DevOps 180

DevOps Analytics Storage Metrics 180

Scalegrid

FEBRUARY 8, 2024

Key Takeaways Distributed storage systems benefit organizations by enhancing data availability, fault tolerance, and system scalability, leading to cost savings from reduced hardware needs, energy consumption, and personnel. Variations within these storage systems are called distributed file systems.

Storage 130

Storage Systems Big Data Azure 130

Percona

MARCH 30, 2023

The use of open source databases has increased steadily in recent years. Past trepidation — about perceived vulnerabilities and performance issues — has faded as decision makers realize what an “open source database” really is and what it offers. What is an open source database?

Open Source 75

Open Source Database Storage Scalability 75

Dynatrace

OCTOBER 23, 2023

This spans from the end user’s experience down to the performance of underlying database queries, and from the application code down to the hardware resources it utilizes. Users of Dynatrace can gain comprehensive insights into every aspect of the application delivery chain. Dynatrace is a platform that satisfies all these criteria.

Efficiency 210

Efficiency Virtualization Hardware Performance 210

Scalegrid

JANUARY 12, 2024

Simply put, it’s the set of computational tasks that cloud systems perform, such as hosting databases, enabling collaboration tools, or running compute-intensive algorithms. Strategic allocation of these resources plays a crucial role in achieving scalability, cost savings, improved performance, and staying ahead of advancements in the field.

Cloud 130

Cloud Virtualization Storage Efficiency 130

The Netflix TechBlog

MARCH 5, 2019

In the People space, our data teams contribute to consolidated systems of record on employees, contractors, partners and talent data to help central teams manage headcount planning, reduce acquisition cost, improve hiring practices, and other people analytics related use-cases. Can we measure the impact of Inclusion and Diversity initiatives?

Infrastructure 182

Infrastructure Cloud Scalability AWS 182

ScaleOut Software

JULY 14, 2021

Whether it’s health-tracking watches, long-haul trucks, or security sensors, extracting value from these devices requires streaming analytics that can quickly make sense of the telemetry and intelligently react to handle an emerging issue or capture a new opportunity.

IoT 52

IoT Azure Analytics Serverless 52

Dynatrace

FEBRUARY 15, 2023

Not only are these approaches difficult and costly to maintain, they also lack proper security and scalability. App developers have the same limitless possibilities for creating customized analytics and integrations in any IT environment, whether in the cloud or on-premises.

Government 161

Government Serverless Analytics Metrics 161

ScaleOut Software

AUGUST 5, 2020

And how are they different from streaming pipelines like Azure Stream Analytics and Apache Flink/Beam? What Problems Does Streaming Analytics Solve? To understand why we need real-time digital twins for streaming analytics, we first need to look at what problems are tackled by popular streaming platforms.

Analytics 69

Analytics Azure Processing Speed 69

Dynatrace

MAY 17, 2023

The next level of observability: OneAgent In the first two parts of our series, we used OpenTelemetry to manually instrument our application and send the telemetry data straight to the Dynatrace analytics back end. Database monitoring Once more, under Applications & Microservices, we’ll also find Databases.

Metrics 168

Metrics Monitoring Database Network 168

ScaleOut Software

JANUARY 31, 2020

Consider the typical, conventional streaming analytics pipeline available on popular cloud platforms: A conventional pipeline combines telemetry from all data sources into a single stream which is queried by the user’s streaming analytics application. It’s simply not practical to create a unique query tailored for each data source.

Analytics 59

Analytics Social Media Ecommerce Serverless 59

Dynatrace

JANUARY 5, 2022

To do so we have successfully established AI-based White box load and resiliency testing with JMeter and Dynatrace, helping identify and resolve major performance and scalability problems in recent projects before deploying to production. Each step is automated from provisioning infrastructure to problem analysis.

Testing 214

Testing Open Source Metrics Infrastructure 214

ScaleOut Software

JANUARY 31, 2020

Consider the typical, conventional streaming analytics pipeline available on popular cloud platforms: A conventional pipeline combines telemetry from all data sources into a single stream which is queried by the user’s streaming analytics application. It’s simply not practical to create a unique query tailored for each data source.

Analytics 52

Analytics Social Media Serverless Cloud 52

High Scalability

FEBRUARY 17, 2021

This is guest post by Sachin Sinha who is passionate about data, analytics and machine learning at scale. This article is to simply report the YCSB bench test results in detail for five NoSQL databases namely Redis, MongoDB, Couchbase, Yugabyte and BangDB and compare the result side by side. Author & founder of BangDB. About YCSB.

Benchmarking 308

Benchmarking Latency C++ Database 308

The Morning Paper

SEPTEMBER 10, 2019

Procella: unifying serving and analytical data at YouTube Chattopadhyay et al., Broadly, these can be categorized as: reporting and dashboarding, embedded statistics in pages, time-series monitoring, and ad-hoc analysis. VLDB’19. Typically, organizations build specialized infrastructure for each of these use cases. are divided.

Analytics 75

Analytics Latency Cache Google 75

Dynatrace

SEPTEMBER 29, 2021

This opens the door to auto-scalable applications, which effortlessly matches the demands of rapidly growing and varying user traffic. The true power of Kubernetes comes with its almost limitless scalability, configurability, and rich technology ecosystem including many open-source frameworks for monitoring, management, and security.

Open Source 297

Open Source Traffic DevOps Cloud 297

Dynatrace

NOVEMBER 3, 2021

For example, when monitoring a database, you’ll want to know about any latency when writing data to a disk or average query response time. Experienced database administrators learn to spot patterns that can lead to common problems. Organizations look to observability to provide the data they need for contextual analysis.

Monitoring 216

Monitoring Metrics DevOps Scalability 216

Dynatrace

APRIL 1, 2021

The benefit is scalability. Logs can extend your cloud observability beyond simple analysis,” Franczak said. The DS database had been reconfigured, which impacted 400 users. The DS database had been reconfigured, which impacted 400 users. He outlined another scenario involving BigQuery, a GCP analytics service.

Azure 170

Azure AWS DevOps Cloud 170

ScaleOut Software

JULY 19, 2021

Real-Time Device Tracking with In-Memory Computing Can Fill an Important Gap in Today’s Streaming Analytics Platforms. The Limitations of Today’s Streaming Analytics. How are we managing the torrent of telemetry that flows into analytics systems from these devices? The list goes on.

IoT 78

IoT Analytics Big Data Architecture 78

ScaleOut Software

NOVEMBER 24, 2020

Real-Time Digital Twins Can Add Important New Capabilities to Telematics Systems and Eliminate Scalability Bottlenecks. Every few seconds, the application servers collect batches of snapshots and write them to the database where they can be queried by dispatchers managing the fleet.

Analytics 52

Analytics Architecture Scalability Software Architecture 52

Dynatrace

DECEMBER 8, 2020

It inherits the automation, AI, scalability, and enterprise-grade robustness of the Dynatrace platform. With new RASP capabilities of the Dynatrace OneAgent, the same trusted approach extends the Dynatrace platform to application security: automatic, intelligent, highly scalable.

Cloud 287

Cloud Open Source Internet Internet 287

Percona

JANUARY 14, 2019

What if we use ClickHouse (which is a columnar analytical database) as our main datastore? Well, typically, an analytical database is not a replacement for a transactional or key/value datastore. This information can be a mix of analytical (OLAP) queries (i.e. So can we use it as our main datastore? Processed 4.15

Database 40

Database Analytics Blockchain Healthcare 40

ScaleOut Software

MAY 6, 2020

Writing applications for streaming analytics can be complex and time consuming. In most cases, applications just export interesting patterns for visualization or offline analysis. Existing programming models make it too difficult to perform meaningful analysis in real time. A visualization tool that displays key statistics.

Development 52

Development Analytics Database Programming 52

ScaleOut Software

MAY 6, 2020

Writing applications for streaming analytics can be complex and time consuming. In most cases, applications just export interesting patterns for visualization or offline analysis. Existing programming models make it too difficult to perform meaningful analysis in real time. A visualization tool that displays key statistics.

Development 52

Development Analytics Database Programming 52

Percona

DECEMBER 14, 2022

In the database world there are essentially two types of database operations: Online Transaction Processing , OLTP : Online transaction processing applications have high throughput and are insert- or update-intensive in database management. What follows here are the results of my analysis. OLTP vs OLAP. drill-down.

Database 92

Database Analytics Storage Processing 92

ScaleOut Software

APRIL 3, 2020

An innovative new software approach called “real-time digital twins” running on a cloud-hosted, highly scalable, in-memory computing platform can help address this challenge. Within seconds, the software performs aggregate analysis of this data for all real-time digital twins.

Logistics 52

Logistics Analytics Scalability Cloud 52

ScaleOut Software

APRIL 3, 2020

An innovative new software approach called “real-time digital twins” running on a cloud-hosted, highly scalable, in-memory computing platform can help address this challenge. Within seconds, the software performs aggregate analysis of this data for all real-time digital twins.

Logistics 52

Logistics Analytics Scalability Cloud 52

Dynatrace

SEPTEMBER 17, 2019

Cluster and container Log Analytics. Another important view is the historical data across all nodes, which allows administrators to spot deployment imbalances as well as under or overprovisioned nodes: The node analysis view makes it easy to spot deployment imbalances as well as misconfigured and unhealthy nodes. #3 3 Log Analytics.

AWS 127

AWS Monitoring Ecommerce Lambda 127

ScaleOut Software

JANUARY 9, 2020

Traditional platforms for streaming analytics don’t offer the combination of granular data tracking and real-time aggregate analysis that logistics applications in operational environments such as these require. With the real-time digital twin model, the next generation of streaming analytics has arrived.

Logistics 52

Logistics Retail Analytics Azure 52

ScaleOut Software

JANUARY 9, 2020

Traditional platforms for streaming analytics don’t offer the combination of granular data tracking and real-time aggregate analysis that logistics applications in operational environments such as these require. With the real-time digital twin model, the next generation of streaming analytics has arrived.

Logistics 52

Logistics Retail Analytics Azure 52

ScaleOut Software

JANUARY 9, 2020

Traditional platforms for streaming analytics don’t offer the combination of granular data tracking and real-time aggregate analysis that logistics applications such as these require. It’s not enough to just pick out interesting events from an aggregated data stream and then send them to a database for offline analysis using Spark.

Logistics 52

Logistics Retail Analytics Azure 52

ScaleOut Software

MAY 19, 2020

Today ScaleOut Software announces the release of its ground-breaking cloud service for streaming analytics using the real-time digital twin model. Traditional platforms for streaming analytics attempt to look at the entire telemetry pipeline using techniques such as SQL query to uncover and act on patterns of interest.

Logistics 52

Logistics IoT Analytics Azure 52

ScaleOut Software

MAY 19, 2020

Today ScaleOut Software announces the release of its ground-breaking cloud service for streaming analytics using the real-time digital twin model. Traditional platforms for streaming analytics attempt to look at the entire telemetry pipeline using techniques such as SQL query to uncover and act on patterns of interest.

Logistics 52

Logistics IoT Analytics Azure 52

The Netflix TechBlog

MAY 21, 2019

Solution We built a system called Lerner that consists of a set of microservices and a python library that allows scalable agent training and inference for test case scheduling. We needed a way to run agents and tie the runs to the internal infrastructure for analytics, reporting, and visualizations.

Testing 163

Testing AWS Lambda Network 163