Dynatrace

MAY 3, 2024

Real-time streaming needs real-time analytics As enterprises move their workloads to cloud service providers like Amazon Web Services, the complexity of observing their workloads increases. SREs and DevOps engineers need cloud logs in an integrated observability platform to monitor the whole software development lifecycle.

Cloud 261

Cloud Lambda AWS Analytics 261

Dynatrace

APRIL 5, 2024

For example, suppose a company has standardized on a suite of disparate tools to monitor its infrastructure and apps. This enables companies to ingest, analyze, and retain massive quantities of data with powerful analytics and AI-powered answers. Choosing the right observability solution is critical to success in this model.

Cloud 246

Cloud Analytics Monitoring Scalability 246

Dynatrace

NOVEMBER 2, 2022

Why organizations are turning to software development to deliver business value. Digital immunity has emerged as a strategic priority for organizations striving to create secure software development that delivers business value. Software development success no longer means just meeting project deadlines. Autonomous testing.

Software 205

Software Software Artificial Intelligence DevOps 205

Dynatrace

APRIL 18, 2024

DevOps and platform engineering are essential disciplines that provide immense value in the realm of cloud-native technology and software delivery. The deep visibility and insights that observability provides allow teams to take proactive measures early in the software development life cycle (SDLC).

DevOps 199

DevOps Engineering Artificial Intelligence Infrastructure 199

Dynatrace

FEBRUARY 10, 2023

In what follows, we explore some key cloud observability trends in 2023, such as workflow automation and exploratory analytics. From data lakehouse to an analytics platform Traditionally, to gain true business insight, organizations had to make tradeoffs between accessing quality, real-time data and factors such as data storage costs.

Efficiency 285

Efficiency Performance Analytics DevOps 285

Dynatrace

NOVEMBER 17, 2020

An effective solution to this problem must be able to handle scale, depth, breadth, and heterogeneity across the software lifecycle. The seamless integration enables enrichment of your OpenTelemetry metrics and traces with insights from the Dynatrace Software Intelligence Platform. This is where Dynatrace comes into play.

Analytics 161

Analytics Technology Technology Cloud 161

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

APRIL 20, 2023

Causal AI—which brings AI-enabled actionable insights to IT operations—and a data lakehouse, such as Dynatrace Grail , can help break down silos among ITOps, DevSecOps, site reliability engineering, and business analytics teams. This equates to 26,000 customer logins per minute at peak demand times.

Analytics 196

Analytics Infrastructure Storage Efficiency 196

Dynatrace

APRIL 25, 2023

Innovating with software is happening faster than ever. The traditional practice of scanning for vulnerabilities before production is insufficient because vulnerabilities can emerge at any point in the software supply chain. Ensuring secure applications amid rising complexity is a crucial part of this journey.

Government 222

Government Innovation Open Source Traffic 222

Dynatrace

JANUARY 22, 2024

For example, machine learning can identify correlations in data and generate predictions, while causal AI determines which ones are the true drivers. Software development. Software project managers can optimize development processes by analyzing workflow data, such as development time, code commits, and testing phases.

Artificial Intelligence 217

Artificial Intelligence Healthcare Retail Government 217

Dynatrace

JUNE 27, 2023

We hear from our customers how important it is to have a centralized, quick, and powerful access point to analyze these logs; hence we’re making it easier to ingest AWS S3 logs and leverage Dynatrace Log Management and Analytics powered by Grail.

AWS 208

AWS Cloud Lambda Analytics 208

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. These distributed storage services also play a pivotal role in big data and analytics operations.

Storage 130

Storage Systems Big Data Azure 130

ScaleOut Software

JULY 21, 2020

ScaleOut StateServer® Pro Adds Analytics to In-Memory Data Grids . Designed to help scalable applications deliver high performance, it stores live, fast-changing data in memory (DRAM) for fast updates and retrieval. It also transparently makes use of the IMDG’s scalable computing resources to accelerate the analysis.

Analytics 52

Analytics Airlines Cache Scalability 52

Dynatrace

SEPTEMBER 8, 2022

Event logging and software tracing help application developers and operations teams understand what’s happening throughout their application flow and system. While logging is the act of recording logs, organizations extract actionable insights from these logs with log monitoring, log analytics, and log management.

Systems 193

Systems Cloud Analytics DevOps 193

ScaleOut Software

JULY 21, 2020

ScaleOut StateServer® Pro Adds Analytics to In-Memory Data Grids . Designed to help scalable applications deliver high performance, it stores live, fast-changing data in memory (DRAM) for fast updates and retrieval. It also transparently makes use of the IMDG’s scalable computing resources to accelerate the analysis.

Analytics 52

Analytics Airlines Cache Scalability 52

ScaleOut Software

JUNE 15, 2020

When analyzing telemetry from a large population of data sources, such as a fleet of rental cars or IoT devices in “smart cities” deployments, it’s difficult if not impossible for conventional streaming analytics platforms to track the behavior of each individual data source and derive actionable information in real time.

Analytics 52

Analytics IoT Lambda Big Data 52

Dynatrace

FEBRUARY 15, 2023

But to be scalable, they also need low-code/no-code solutions that don’t require a lot of spin-up or engineering expertise. Development teams need automated workflows so they’re not stuck manually monitoring all stages of the software development lifecycle in their cloud environments.

Code 221

Code DevOps Cloud Analytics 221

ScaleOut Software

JANUARY 31, 2020

Real-time digital twins offer a compelling new software model for tracking and analyzing telemetry from large numbers of data sources. These query results are then forwarded to a data lake for offline analytics using tools such as Spark and for data visualization.

Analytics 59

Analytics Social Media Ecommerce Serverless 59

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 171

Government Serverless Analytics Metrics 171

ScaleOut Software

JUNE 15, 2020

When analyzing telemetry from a large population of data sources, such as a fleet of rental cars or IoT devices in “smart cities” deployments, it’s difficult if not impossible for conventional streaming analytics platforms to track the behavior of each individual data source and derive actionable information in real time.

Analytics 52

Analytics IoT Lambda Big Data 52

Scalegrid

JANUARY 12, 2024

Various forms can take shape when discussing workloads within the realm of cloud computing environments – examples include order management databases, collaboration tools, videoconferencing systems, virtual desktops, and disaster recovery mechanisms. This also aids scalability down the line.

Cloud 130

Cloud Virtualization Storage Efficiency 130

High Scalability

JANUARY 11, 2022

We have chosen this NoSQL based solution over relational databases as it provides the scalability to have hierarchies which go beyond two levels and extensibility due to the schema-less behavior of NoSQL data storage. For example, one user is a close follower of Elon Musk while another user can be a close follower of Gordon Ramsay.

Design 334

Design Media Storage Logistics 334

ScaleOut Software

JANUARY 31, 2020

Real-time digital twins offer a compelling new software model for tracking and analyzing telemetry from large numbers of data sources. These query results are then forwarded to a data lake for offline analytics using tools such as Spark and for data visualization.

Analytics 52

Analytics Social Media Serverless Cloud 52

Dynatrace

JULY 24, 2023

In the world of DevOps and SRE, DevOps automation answers the undeniable need for efficiency and scalability. For example, consider an e-commerce website that automatically sends personalized discount codes to customers who abandon their shopping carts. DevOps teams need automation that goes beyond passive observations.

DevOps 228

DevOps Traffic Efficiency Servers 228

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

Scalegrid

DECEMBER 21, 2023

They may even help develop personalized web analytics software as well as leverage Hashes, Bitmaps, or Streams from Redis Data Types into a wider scope of applications such as analytic operations. Examples include slow command execution time which leads to poor latency and increased memory usage.

Strategy 130

Strategy Monitoring Latency DevOps 130

Dynatrace

DECEMBER 21, 2023

And while these examples were resolved by just asking a few questions, in many cases, the answers are more elusive, requiring real-time and historical drill-downs into the processes and dependencies specific to each host. A few examples: Reduce roundtrips between services (for example, the N+1 query pattern).

Cloud 218

Cloud Energy Best Practices Cache 218

Dynatrace

DECEMBER 5, 2023

Legacy data center infrastructure and software support have kept all the benefits of ARM at, well… arm’s length. But take a look at the latest iterations of, for example, AWS Graviton2, which delivered a 40% price/performance boost, and Graviton3, which had an additional 27% price/performance improvement over Graviton2.

Efficiency 274

Efficiency Architecture Energy Monitoring 274

Dynatrace

JULY 11, 2023

Dynatrace full stack Red Hat OpenShift observability Dynatrace unifies platform engineering and application teams on a single platform, enhancing software quality and operational efficiency to drive innovation. Having all data in context tremendously simplifies analytics and problem detection.

Architecture 176

Architecture Availability Infrastructure Monitoring 176

Dynatrace

JANUARY 23, 2024

AI data analysis can help development teams release software faster and at higher quality. Another key theme at Dynatrace Perform 2024 is organizations’ growing adoption of platform engineering , which helps accelerate the delivery of software applications.

Performance 195

Performance DevOps Innovation Artificial Intelligence 195

Dynatrace

OCTOBER 7, 2020

Open-source metric sources automatically map to our Smartscape model for AI analytics. Here’s a quick overview of what you can achieve now that the Dynatrace Software Intelligence Platform has been extended to ingest third-party metrics. For example, StatsD doesn’t support dimensions and tagging.

Open Source 260

Open Source Metrics Analytics Tuning 260

Dynatrace

AUGUST 25, 2023

For example, older systems may require additional support personnel or contractors to operate and maintain. The team can also focus on developing new cloud-native apps that provide the scalability necessary to deliver reliable services, especially during times of crisis when families need HHS the most.

Government 213

Government Infrastructure Programming Cloud 213

Dynatrace

OCTOBER 8, 2020

They may be used to, for example, integrate a new payment service or create a new interface for a booking platform. Although the adoption of serverless functions brings many benefits, including scalability, quick deployments, and updates, it also introduces visibility and monitoring challenges to CloudOps and DevOps.

Lambda 304

Lambda AWS Programming Serverless 304

Dynatrace

SEPTEMBER 29, 2021

Just like shipping containers revolutionized the transportation industry, Docker containers disrupted software. A standard Docker container can run anywhere, on a personal computer (for example, PC, Mac, Linux), in the cloud, on local servers, and even on edge devices. Here are some examples. What is Docker? Kubernetes.

Open Source 310

Open Source Traffic DevOps Cloud 310

Dynatrace

OCTOBER 17, 2023

Grail is designed for scalability, with no technical prerequisites or additional hosting and storage costs as ingestion rates increase. This phase covers bringing your data into Dynatrace software as a service (SaaS) via whichever ingestion channel or method. For example, this includes the following: Click to query.

Retail 246

Retail Storage Best Practices Architecture 246

Dynatrace

NOVEMBER 22, 2021

If a user encounters an error page on a website, for example, it’s vital to trace the behavior to the original source of failure. To gain insight into these problems, software engineers typically deploy application instrumentation frameworks that provide insight into applications and code. AWS monitoring best practices.

Best Practices 220

Best Practices AWS Monitoring Serverless 220

Percona

MARCH 30, 2023

In fact, the opposite is true, thanks to an active and vibrant global community of developers who work continuously to improve open source software. For example, an analytics application would work best with unstructured image files stored in a non-relational graph database.

Open Source 75

Open Source Database Storage Scalability 75