Dynatrace

DECEMBER 5, 2023

Streamline privacy requirements with flexible retention periods Data retention is a critical aspect of data handling, and it’s not just about privacy compliance—it’s about having the flexibility to optimize data storage times in Grail for your Dynatrace use cases.

Storage 168

Storage Healthcare Best Practices Speed 168

Dynatrace

JUNE 9, 2023

ln a world driven by macroeconomic uncertainty, businesses increasingly turn to data-driven decision-making to stay agile. 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. All of these factors challenge DevOps maturity.

DevOps 186

DevOps Analytics Storage Metrics 186

Dynatrace

OCTOBER 14, 2022

Log data provides a unique source of truth for debugging applications, optimizing infrastructure, and investigating security incidents. This contextualization of log data enables AI-powered problem detection and root cause analysis at scale. Dynamic landscape and data handling requirements result in manual work.

Storage 229

Storage Government Network Infrastructure 229

Percona

FEBRUARY 10, 2023

ViewBlock , a blockchain explorer, uses the Percona Operator for MongoDB to store critical data. Today along with their team, we will see how pvc-autoresizer can automate storage scaling for MongoDB clusters on Kubernetes. In our lab we will use AWS EKS with a standard storage class. Note : If you use version 1.14.0

Storage 114

Storage Blockchain AWS Cloud 114

DZone

JULY 3, 2023

Data engineering projects often require the setup and management of complex infrastructures that support data processing, storage, and analysis. Traditionally, this process involved manual configuration, leading to potential inconsistencies, human errors, and time-consuming deployments.

Data Engineering 141

Data Engineering Infrastructure Engineering Code 141

DZone

JANUARY 16, 2023

BindPlane OP is a powerful open-source tool that makes it easy to build and manage telemetry pipelines to ship data from IT environments of any kind and size to any analysis tool or storage destination. The vendor-agnostic toolset is excellent for reducing data costs and getting the most out of your data.

Open Source 204

Open Source Storage Processing 204

Dynatrace

SEPTEMBER 5, 2023

Predictive AI uses machine learning, data analysis, statistical models, and AI methods to predict anomalies, identify patterns, and create forecasts. Through predictive analytics, SREs and DevOps engineers can accurately forecast resource needs based on historical data. Proactive resource allocation. Capacity planning.

Artificial Intelligence 265

Artificial Intelligence DevOps Analytics Engineering 265

Dynatrace

JANUARY 23, 2024

AI data analysis can help development teams release software faster and at higher quality. So how can organizations ensure data quality, reliability, and freshness for AI-driven answers and insights? And how can they take advantage of AI without incurring skyrocketing costs to store, manage, and query data?

Performance 188

Performance DevOps Innovation Artificial Intelligence 188

Dynatrace

MAY 7, 2024

Fluent Bit is a telemetry agent designed to receive data (logs, traces, and metrics), process or modify it, and export it to a destination. Fluent Bit can serve as a proxy before you send data to Dynatrace or similar. However, you can also use Fluent Bit as a processor because you can perform various actions on the data.

Best Practices 171

Best Practices IoT Metrics Storage 171

Scalegrid

JANUARY 19, 2024

When a MongoDB rollback happens, it can cause trouble to your data integrity and system consistency. Understanding how to address a rollback is critical for minimizing potential data loss and maintaining seamless operations. With direct, actionable insights, prepare to navigate the complexities of rollbacks with confidence.

Database 130

Database Network Servers Monitoring 130

The Netflix TechBlog

OCTOBER 28, 2021

Data Engineers of Netflix?—?Interview Interview with Pallavi Phadnis This post is part of our “ Data Engineers of Netflix ” series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. Pallavi Phadnis is a Senior Software Engineer on the Product Data Science and Engineering team.

Data Engineering 173

Data Engineering Engineering Big Data Software Engineering 173

Dynatrace

APRIL 24, 2024

To transparently manage expectations and maintain trust with our customers, we expanded the Dynatrace SLA beyond accessing the user interface to cover the full range of relevant product categories, such as processing and retaining incoming data, accessing and working with data, and triggering automations.

Azure 242

Azure Infrastructure Metrics AWS 242

Highly Scalable

AUGUST 20, 2013

The shortcomings and drawbacks of batch-oriented data processing were widely recognized by the Big Data community quite a long time ago. It became clear that real-time query processing and in-stream processing is the immediate need in many practical applications. Modularity and flexibility.

Big Data 154

Big Data Processing Lambda Database 154

The Netflix TechBlog

OCTOBER 15, 2019

Part I: Overview Andreas Andreakis , Falguni Jhaveri , Ioannis Papapanagiotou , Mark Cho , Poorna Reddy , Tongliang Liu Overview It is a commonly observed pattern for applications to utilize multiple datastores where each is used to serve a specific need such as storing the canonical form of data (MySQL etc.), caching (Memcached etc.),

Transportation 192

Transportation Architecture Processing Storage 192

DZone

JUNE 4, 2019

NVMe Storage Use Cases. NVMe storage's strong performance, combined with the capacity and data availability benefits of shared NVMe storage over local SSD, makes it a strong solution for AI/ML infrastructures of any size. There are several AI/ML focused use cases to highlight.

Storage 100

Storage FinTech Artificial Intelligence Performance 100

Dynatrace

OCTOBER 17, 2023

In today’s data-driven landscape, businesses are grappling with an unprecedented surge in data volume. The data generated by applications to support operational teams has reached overwhelming proportions. This data overload also prevents customer-centric pricing models as users consider cost-effective technology platforms.

Retail 239

Retail Storage Best Practices Architecture 239

DZone

NOVEMBER 25, 2023

We often dwell on the technical aspects of database selection, focusing on performance metrics , storage capacity, and querying capabilities. Factors like read and write speed, latency, and data distribution methods are essential. In a detailed article, we've discussed how to align a NoSQL database with specific business needs.

Database 268

Database Latency Speed Metrics 268

Dynatrace

MAY 14, 2020

Dynatrace just makes this easy—it comes out-of-the-box, no silos of data, no DIY stitching together tools, no wasted time, and no wasted resources. . A Dynatrace Managed cluster may lack the necessary hardware to process all the additional incoming data. Please watch disk space usage and extend it if needed.

Processing 155

Processing Hardware Traffic Storage 155

Dynatrace

SEPTEMBER 23, 2020

Recent improvements in OneAgent runtime-data handling. Storage mount points in a system might be larger or smaller, local or remote, with high or low latency, and various speeds. Starting with OneAgent version 1.199, the runtime folder is configurable and consequently you can retain your storage mount point setup as-is.

Storage 148

Storage Latency Operating System Network 148

DZone

OCTOBER 24, 2023

The ELK stack is an abbreviation for Elasticsearch, Logstash, and Kibana, which offers the following capabilities: Elasticsearch: a scalable search and analytics engine with a log analytics tool and application-formed database, perfect for data-driven applications.

Analytics 255

Analytics Storage Infrastructure Scalability 255

The Morning Paper

MARCH 8, 2020

Building an elastic query engine on disaggregated storage , Vuppalapati, NSDI’20. This paper describes the design decisions behind the Snowflake cloud-based data warehouse. An increasingly large fraction of data in modern workloads comes from less predictable and highly variable sources. joins) during query processing.

Storage 112

Storage Engineering Cache Serverless 112

High Scalability

JANUARY 11, 2022

from a client it performs two parallel operations: i) persisting the action in the data store ii) publish the action in a streaming data store for a pub-sub model. User Feed Service, Media Counter Service) read the actions from the streaming data store and performs their specific tasks. After that, the various services (e.g.

Design 334

Design Media Storage Logistics 334

DZone

AUGUST 16, 2023

Caching is the process of storing frequently accessed data or resources in a temporary storage location, such as memory or disk, to improve retrieval speed and reduce the need for repetitive processing.

Cache 246

Cache Scalability Performance Latency 246

DZone

JUNE 6, 2023

When building an IoT-based service, we need to implement a messaging mechanism that transmits data collected by the IoT devices to a hub or a server. When dealing with IoT, one of the first things that come to mind is the limited processing, networking, and storage capabilities these devices operate with.

IoT 293

IoT Tuning Storage Network 293

Dynatrace

OCTOBER 30, 2023

Data proliferation and the increased complexity of modern multicloud environments are nearly impossible to manage without automation. Unified observability and security in the development process are crucial to defining ownership in the development process. Dynatrace AutomationEngine fully automates this entire process.

Engineering 247

Engineering DevOps Innovation Storage 247

DZone

MAY 5, 2023

Apache Kafka and Apache Flink are increasingly joining forces to build innovative real-time stream processing applications. The Tremendous Adoption of Apache Kafka and Apache Flink Apache Kafka became the de facto standard for data streaming.

Open Source 246

Open Source Storage Innovation Engineering 246

Dynatrace

MARCH 6, 2024

They create an explosion of data that is extremely challenging to manually capture, analyze, and act on. Manual monitoring processes are also too time-consuming, which distracts teams from tasks that create new value for customers and the business. But these environments are, by nature, difficult to manage.

Analytics 193

Analytics Innovation Strategy Storage 193

Dynatrace

APRIL 8, 2024

Optimize the IT infrastructure supporting risk management processes and controls for maximum performance and resilience. The IT infrastructure, services, and applications that enable processes for risk management must perform optimally. Deploy risk-based estimates and models with confidence, accuracy, transparency, and speed.

Analytics 203

Analytics Infrastructure Efficiency Technology 203

Percona

APRIL 14, 2023

A shared characteristic in most (if not all) databases, be them traditional relational databases like Oracle, MySQL, and PostgreSQL or some kind of NoSQL-style database like MongoDB, is the use of a caching mechanism to keep (a copy of) part of the data in memory. So, how do you know if your hot data is in memory? MySQL does.

Cache 94

Cache Efficiency Database Monitoring 94

DZone

JUNE 15, 2023

It is worth noting that this data collection process does not impact the performance of the application. Moreover, the process of collecting these profiles introduces overhead during application runtime and necessitates the storage and visualization of significantly large datasets.

Latency 246

Latency Storage Strategy Metrics 246

Dynatrace

JULY 29, 2022

Log analytics is the process of viewing, interpreting, and querying log data so developers and IT teams can quickly detect and resolve application and system issues. At the same time, log analytics can present challenges as data volumes explode, particularly in traditional environments that lack end-to-end observability solutions.

Analytics 217

Analytics Storage Retail Monitoring 217

Dynatrace

OCTOBER 23, 2023

Hyper-V plays a vital role in ensuring the reliable operations of data centers that are based on Microsoft platforms. Secondly, determining the correct allocation of resources (CPU, memory, storage) to each virtual machine to ensure optimal performance without over-provisioning can be difficult. What is Microsoft Hyper-V?

Efficiency 216

Efficiency Virtualization Hardware Performance 216

DZone

DECEMBER 14, 2021

Metadata synchronization (sync) is a core feature in Alluxio that keeps files and directories consistent with their source of truth in under-storage systems, thus making it simple for users to reason the data retrieved from Alluxio. Meanwhile, understanding the internal process is important in order to tune the performance.

Design 244

Design Storage Tuning Systems 244

DZone

JANUARY 31, 2024

SIEM platforms streamline incident response processes, allowing security teams to respond quickly and effectively to security incidents. SIEM systems enable early detection of security threats and suspicious activities by analyzing vast amounts of log data in real time. This helps in detecting threats and attacks in real time.

Storage 136

Storage Data Engineering Network Infrastructure 136

Dynatrace

JULY 29, 2022

Log analytics is the process of viewing, interpreting, and querying log data so developers and IT teams can quickly detect and resolve application and system issues. At the same time, log analytics can present challenges as data volumes explode, particularly in traditional environments that lack end-to-end observability solutions.

Analytics 183

Analytics Storage Retail Monitoring 183

Percona

MARCH 21, 2023

We want to improve our ability to replicate your data and limit replication to row-based events securely, wherein we do not have control over the source(s). The replica doesn’t have checking capabilities when processing replicated transactions as of MySQL 8.0.18. It does this to carry out all instructions from its upstream.

Storage 91

Storage Open Source Database Engineering 91

Smashing Magazine

SEPTEMBER 28, 2022

Five Data-Loading Patterns To Improve Frontend Performance. Five Data-Loading Patterns To Improve Frontend Performance. Every unnecessary bit of JavaScript code you bundle and serve will be more code the client has to load and process. It is important to note how much data the client needs to download. Large preview ).

Cache 125

Cache Performance Servers Social Media 125