Dynatrace

OCTOBER 17, 2023

The rise of cloud-native microservice architectures further exacerbates this change. Dynatrace has developed the purpose-built data lakehouse, Grail , eliminating the need for separate management of indexes and storage. All data is readily accessible without storage tiers, such as costly solid-state drives (SSDs).

Retail 235

Retail Storage Best Practices Architecture 235

Dynatrace

DECEMBER 16, 2022

AI-powered precise answers and timely insights with ad-hoc analytics. Successful platform adoption requires a platform to be easy to use and integrate with other architectures, applications, and data sources. With open standards, developers can take a Lego-like approach to application development, which makes delivery more efficient.

Innovation 195

Innovation Software Software Cloud 195

Dynatrace

SEPTEMBER 13, 2023

This is a set of best practices and guidelines that help you design and operate reliable, secure, efficient, cost-effective, and sustainable systems in the cloud. The framework comprises six pillars: Operational Excellence, Security, Reliability, Performance Efficiency, Cost Optimization, and Sustainability.

AWS 245

AWS Efficiency Azure Cloud 245

Dynatrace

JANUARY 23, 2024

AI-enabled chatbots can help service teams triage customer issues more efficiently. Deriving business value with AI, IT automation, and data reliability When it comes to increasing business efficiency, boosting productivity, and speeding innovation, artificial intelligence takes center stage. What is explainable AI?

Performance 184

Performance DevOps Innovation Artificial Intelligence 184

Scalegrid

FEBRUARY 8, 2024

A distributed storage system is foundational in today’s data-driven landscape, ensuring data spread over multiple servers is reliable, accessible, and manageable. Understanding distributed storage is imperative as data volumes and the need for robust storage solutions rise.

Storage 130

Storage Systems Big Data Azure 130

Dynatrace

MARCH 24, 2023

Container technology enables organizations to efficiently develop cloud-native applications or to modernize legacy applications to take advantage of cloud services. This clinic will walk you through Dynatrace’s log monitoring and analytics capabilities, with a specific focus on Kubernetes and cloud-native architectures.

Infrastructure 184

Infrastructure Open Source Operating System Cloud 184

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

Dynatrace

OCTOBER 14, 2022

All this is easier said than done because: Kubernetes-based dynamic architecture is becoming the norm. This allows you to create flexible and powerful log storage configurations on any level by utilizing the unique autodiscovery capabilities of Dynatrace OneAgent or a custom setup. Try it out yourself.

Storage 225

Storage Government Network Infrastructure 225

Dynatrace

DECEMBER 15, 2022

Besides the traditional system hardware, storage, routers, and software, ITOps also includes virtual components of the network and cloud infrastructure. Adding application security to development and operations workflows increases efficiency. The primary goal of ITOps is to provide a high-performing, consistent IT environment.

Artificial Intelligence 201

Artificial Intelligence DevOps Hardware Virtualization 201

Dynatrace

DECEMBER 15, 2022

In this blog, we share three log ingestion strategies from the field that demonstrate how building up efficient log collection can be environment-agnostic by using our generic log ingestion application programming interface (API). In the “Storage and Logging” section, select “ awsfirelens ” as the log driver.

Strategy 179

Strategy AWS Open Source Transportation 179

Dynatrace

DECEMBER 5, 2023

Without observability, the benefits of ARM are lost Over the last decade and a half, a new wave of computer architecture has overtaken the world. ARM architecture, based on a processor type optimized for cloud and hyperscale computing, has become the most prevalent on the planet, with billions of ARM devices currently in use.

Efficiency 264

Efficiency Architecture Energy Monitoring 264

ScaleOut Software

JULY 21, 2020

ScaleOut StateServer® Pro Adds Analytics to In-Memory Data Grids . Because IMDGs have highly scalable storage capacity, they can easily return large numbers of matching objects to the client application, and this leads to network bottlenecks transferring large amounts of data from the IMDG back to the client.

Analytics 52

Analytics Airlines Cache Scalability 52

ScaleOut Software

JULY 21, 2020

ScaleOut StateServer® Pro Adds Analytics to In-Memory Data Grids . Because IMDGs have highly scalable storage capacity, they can easily return large numbers of matching objects to the client application, and this leads to network bottlenecks transferring large amounts of data from the IMDG back to the client.

Analytics 52

Analytics Airlines Cache Scalability 52

Percona

AUGUST 17, 2023

It’s used for data management (shocker), application development, and data analytics. PostgreSQL has powerful and advanced features, including asynchronous replication, full-text searches of the database, and native support for JSON-style storage, key-value storage, and XML. What is PostgreSQL used for?

Open Source 82

Open Source Healthcare Social Media Database 82

Dynatrace

OCTOBER 4, 2022

As a result, organizations need software to work perfectly to create customer experiences, deliver innovation, and generate operational efficiency. Traditionally, though, to gain true business insight, organizations had to make tradeoffs between accessing quality, real-time data and factors such as data storage costs.

Analytics 189

Analytics Software Software Storage 189

Dynatrace

FEBRUARY 15, 2023

A modern observability and analytics platform brings data silos together and facilitates collaboration and better decision-making among teams. But making decisions about which data to store in easily accessible hot storage upfront requires IT pros to know which questions they want to ask ahead of time and ensure that data is indexed.

Analytics 130

Analytics Storage Cloud DevOps 130

Dynatrace

OCTOBER 4, 2022

Log management and analytics is an essential part of any organization’s infrastructure, and it’s no secret the industry has suffered from a shortage of innovation for several years. Several pain points have made it difficult for organizations to manage their data efficiently and create actual value.

Analytics 233

Analytics Artificial Intelligence Storage Serverless 233

Dynatrace

FEBRUARY 16, 2023

Grail combines the big-data storage of a data warehouse with the analytical flexibility of a data lake. With Grail, we have reinvented analytics for converged observability and security data,” Greifeneder says. Logs on Grail Log data is foundational for any IT analytics. Grail and DQL will give you new superpowers.”

Analytics 184

Analytics Innovation Metrics Database 184

ScaleOut Software

JANUARY 9, 2020

To keep operations efficient and cost-effective, it’s important to be able to quickly respond to issues as they occur and efficiently verify their resolution. In addition, the platform provides fast, in-memory data storage so that the application can easily and quickly record both telemetry and analytics results for each store.

Logistics 52

Logistics Retail Analytics Azure 52

ScaleOut Software

JANUARY 9, 2020

To keep operations efficient and cost-effective, it’s important to be able to quickly respond to issues as they occur and efficiently verify their resolution. In addition, the platform provides fast, in-memory data storage so that the application can easily and quickly record both telemetry and analytics results for each store.

Logistics 52

Logistics Retail Analytics Azure 52

ScaleOut Software

JANUARY 9, 2020

To keep operations efficient and cost-effective, it’s important to be able to quickly respond to issues as they occur and efficiently verify their resolution. In addition, the platform provides fast, in-memory data storage so that the application easily can keep track of both telemetry and analytics results for each store.

Logistics 52

Logistics Retail Analytics Azure 52

Dynatrace

OCTOBER 4, 2022

Grail needs to support security data as well as business analytics data and use cases. With that in mind, Grail needs to achieve three main goals with minimal impact to cost: Cope with and manage an enormous amount of data —both on ingest and analytics. Grail architectural basics. Work with different and independent data types.

Artificial Intelligence 266

Artificial Intelligence Analytics Storage Architecture 266

Dynatrace

NOVEMBER 15, 2021

Log monitoring, log analysis, and log analytics are more important than ever as organizations adopt more cloud-native technologies, containers, and microservices-based architectures. What is log analytics? Log analytics is the process of evaluating and interpreting log data so teams can quickly detect and resolve issues.

Analytics 207

Analytics Monitoring Artificial Intelligence DevOps 207

Scalegrid

MARCH 28, 2024

Key Takeaways Redis offers complex data structures and additional features for versatile data handling, while Memcached excels in simplicity with a fast, multi-threaded architecture for basic caching needs. Snapshots provide point-in-time captures of the dataset, which are efficient for recovery on startup.

Cache 130

Cache Storage Scalability Architecture 130

Dynatrace

OCTOBER 4, 2022

These traditional approaches to log monitoring and log analytics thwart IT teams’ goal to address infrastructure performance problems, security threats, and user experience issues. Further, these resources support countless Kubernetes clusters and Java-based architectures. where an error occurred at the code level.

Analytics 219

Analytics Storage Infrastructure Metrics 219

Dynatrace

NOVEMBER 20, 2023

The first goal is to demonstrate how generative AI can bring key business value and efficiency for organizations. While technologies have enabled new productivity and efficiencies, customer expectations have grown exponentially, cyberthreat risks continue to mount, and the pace of business has sped up. What is predictive AI?

AWS 207

AWS Artificial Intelligence Analytics Cloud 207

The Netflix TechBlog

JULY 30, 2019

Many of the Netflix Content and Studio Engineering services rely on Conductor for efficient processing of their business flows. External Payload Storage External payload storage was implemented to prevent the usage of Conductor as a data persistence system and to reduce the pressure on its backend datastore.

Lambda 189

Lambda Media Open Source Metrics 189

Dynatrace

APRIL 20, 2023

With more automated approaches to log monitoring and log analysis, however, organizations can gain visibility into their applications and infrastructure efficiently and with greater precision—even as cloud environments grow. Logs are automatically produced and time-stamped documentation of events relevant to cloud architectures.

Analytics 186

Analytics Infrastructure Storage Efficiency 186

Scalegrid

MARCH 14, 2024

The architecture usually integrates several private, public, and on-premises infrastructures. In practice, a hybrid cloud operates by melding resources and services from multiple computing environments, which necessitates effective coordination, orchestration, and integration to work efficiently.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

The Netflix TechBlog

MAY 21, 2019

There are several problems efficient test scheduling could help us solve: Quickly detect a regression in the integration of the Netflix SDK on a consumer electronic or MVPD (multichannel video programming distributor) device. The data can be truncated after each execution and offloaded to a long-term storage for further analysis.

Testing 163

Testing AWS Lambda Network 163

Scalegrid

MAY 13, 2020

In this blog post, we explain what Greenplum is, and break down the Greenplum architecture, advantages, major use cases, and how to get started. Greenplum Database is an open-source , hardware-agnostic MPP database for analytics, based on PostgreSQL and developed by Pivotal who was later acquired by VMware. The Greenplum Architecture.

Big Data 321

Big Data Database Artificial Intelligence Open Source 321

Dynatrace

OCTOBER 6, 2023

Buckets are similar to folders, a physical storage location. Debug-level logs, which also generate high volumes and have a shorter lifespan or value period than other logs, could similarly benefit from dedicated storage. Suppose a single Grail environment is central storage for pre-production and production systems.

Artificial Intelligence 260

Artificial Intelligence Analytics Metrics Storage 260

Dynatrace

OCTOBER 4, 2022

While data lakes and data warehousing architectures are commonly used modes for storing and analyzing data, a data lakehouse is an efficient third way to store and analyze data that unifies the two architectures while preserving the benefits of both. What is a data lakehouse? How does a data lakehouse work?

Artificial Intelligence 207

Artificial Intelligence Analytics Storage Government 207

Smashing Magazine

NOVEMBER 2, 2021

Cost-Efficient And Effort-Saving Development. On the contrary, a native application of an e-commerce store can come at 30, 50, or even 100 MB and up, consuming internal device storage. The thing is that the majority of Magento stores have been up and running for about a decade and use a monolithic architecture. Large preview ).

Code 74

Code Cache Retail Mobile 74

Scalegrid

DECEMBER 21, 2023

With its widespread use in modern application architectures, understanding the ins and outs of Redis® monitoring is essential for any tech professional. This ensures each Redis® instance optimally uses the in-memory data store and aligns with the operating system’s efficiency.

Strategy 130

Strategy Monitoring Latency DevOps 130

Abhishek Tiwari

JULY 12, 2018

It can be used to power new analytics, insight, and product features. It can be used to power new analytics, insight, and product features. These nodes and edges require a good amount of compute and storage which is typically distributed across a large number servers either running in the cloud or your own data center.

Latency 63

Latency Analytics Scalability Engineering 63

Highly Scalable

AUGUST 20, 2013

The pipelines can be stateful and the engine’s middleware should provide a persistent storage to enable state checkpointing. The engine should be compact and efficient, so one can deploy it in multiple datacenters on small clusters. Efficient lineage tracking is not a trivial problem. Interoperability with Hadoop. Pipelining.

Big Data 154

Big Data Processing Lambda Database 154