Dynatrace

MAY 21, 2024

Masking at storage: Data is persistently masked upon ingestion into Dynatrace. Leverage three masking layers Masking at capture and masking at storage operations exclude targeted sensitive data points. The selected rules can be configured for a whole environment or, more granularly, for specific process groups.

Government 217

Government Storage Tuning Monitoring 217

Percona

JANUARY 4, 2024

Managing storage and performance efficiently in your MySQL database is crucial, and general tablespaces offer flexibility in achieving this. This blog discusses general tablespaces and explores their functionalities, benefits, and practical usage, along with illustrative examples. What are MySQL general tablespaces?

Storage 88

Storage Engineering Database Hardware 88

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 and Fluentd were created for the same purpose: collecting and processing logs, traces, and metrics. Ask yourself, how much data should Fluent Bit process? What is Fluent Bit?

Best Practices 252

Best Practices IoT Metrics Storage 252

Dynatrace

MAY 21, 2024

With the latest advances from Dynatrace, this process is instantaneous. That’s because it does not require any pre-prepared schemas, and access to cold/hot storage is fully automatic and with zero latency. Moreover, it is fast, powered by its massively parallel processing data lakehouse.

Technology 209

Technology Technology Analytics Storage 209

Percona

FEBRUARY 1, 2023

This post will look at using The Oversized-Attribute Storage Technique (TOAST) to improve performance and scalability. This process is done automatically and does not significantly impact how the database is used. text, bytea), and “strategy” is one of the four TOAST storage strategies (PLAIN, EXTENDED, EXTERNAL, MAIN).

Storage 90

Storage Scalability Strategy Performance 90

Dynatrace

MAY 6, 2024

A tight integration between Red Hat Ansible Automation Platform, Dynatrace Davis ® AI, and the Dynatrace observability and security platform enables closed-loop remediation to automate the process from: Detecting a problem. With DQL, the workflow trigger to initiate a required automation and remediation process can be defined.

DevOps 292

DevOps Software Engineering Games Java 292

High Scalability

JANUARY 11, 2022

There are two major processes which gets executed when a user posts a photo on Instagram. Firstly, the synchronous process which is responsible for uploading image content on file storage, persisting the media metadata in graph data-storage, returning the confirmation message to the user and triggering the process to update the user activity.

Design 334

Design Media Storage Logistics 334

Dynatrace

OCTOBER 17, 2023

As a result, IT organizations are overwhelmed as they strive to balance cost control processes with ensuring that their respective organizations have access to all the data required for their various use cases. All data is readily accessible without storage tiers, such as costly solid-state drives (SSDs). Ingest and process.

Retail 245

Retail Storage Best Practices Architecture 245

The Netflix TechBlog

FEBRUARY 13, 2023

We accomplish this by paving the path to: Accessing and processing media data (e.g. To streamline this process, we standardized media assets with pre-processing steps that create and store dedicated quality-controlled derivatives with associated snapshotted metadata. either a movie or an episode within a show).

Media 290

Media Storage Infrastructure Systems 290

Scalegrid

MAY 13, 2020

Greenplum Database is a massively parallel processing (MPP) SQL database that is built and based on PostgreSQL. High performance, query optimization, open source and polymorphic data storage are the major Greenplum advantages. Greenplum uses an MPP database design that can help you develop a scalable, high performance deployment.

Big Data 321

Big Data Database Artificial Intelligence Open Source 321

KeyCDN

FEBRUARY 13, 2020

Push Zones are now seamlessly supporting Image Processing ! The complete feature set of Image Processing is now also available for Push Zones. Our edge servers are directly linked to our global storage cluster, which ensures faster loading times of images. It only takes a few steps to upload and transform images.

Processing 78

Processing Storage Latency Servers 78

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 173

Storage Healthcare Best Practices Speed 173

Dynatrace

MAY 23, 2024

Establishing a single source of truth for all observability data reveals the full power of the Dynatrace platform by querying all data with comprehensive new capabilities from the one Dynatrace Grail data lake house for data storage. Also, see how to automate this process with bicep and how to automate with Azure CLI.

Azure 225

Azure Cloud Metrics Innovation 225

The Netflix TechBlog

SEPTEMBER 24, 2021

By Xiaomei Liu , Rosanna Lee , Cyril Concolato Introduction Behind the scenes of the beloved Netflix streaming service and content, there are many technology innovations in media processing. Packaging has always been an important step in media processing. Uploading and downloading data always come with a penalty, namely latency.

Cloud 237

Cloud Media Storage Cache 237

Dynatrace

OCTOBER 30, 2023

During the session, Reitbauer dove into several business-critical, high-impact examples of how customers can wield platform engineering in the Dynatrace platform out of the box and throughout the entire software delivery lifecycle. Dynatrace AutomationEngine fully automates this entire process. This context arrives automatically.

Engineering 252

Engineering DevOps Innovation Storage 252

Dynatrace

OCTOBER 6, 2023

Buckets are similar to folders, a physical storage location. For example, a separate bucket could be used for detailed logs from Dynatrace Synthetic nodes. 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.

Artificial Intelligence 268

Artificial Intelligence Analytics Metrics Storage 268

Dynatrace

OCTOBER 4, 2022

This architecture offers rich data management and analytics features (taken from the data warehouse model) on top of low-cost cloud storage systems (which are used by data lakes). This decoupling ensures the openness of data and storage formats, while also preserving data in context. Ingest and process with Grail. Retain data.

Artificial Intelligence 275

Artificial Intelligence Analytics Storage Architecture 275

The Morning Paper

JANUARY 28, 2020

Narrowing the gap between serverless and its state with storage functions , Zhang et al., Shredder is " a low-latency multi-tenant cloud store that allows small units of computation to be performed directly within storage nodes. " In from of them is a networking layer, and the in-memory storage layer holds the actual data.

Serverless 99

Serverless Storage Latency Cloud 99

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. In late 2021, for example, digital forensics was central to combating the Log4Shell vulnerability. Cold storage and rehydration. Cold storage and rehydration.

Analytics 223

Analytics Storage Retail Monitoring 223

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. Storage is a critical aspect to consider when working with cloud workloads.

Cloud 130

Cloud Virtualization Storage Efficiency 130

Dynatrace

JANUARY 18, 2023

Let’s look at the unique enabling characteristics of business events through two use case examples, then see how easy it’s to get started. Inventory counts, revenue reports, and service activation flows are just a few examples that demand precision. This diagram shows a few examples of business events.

Analytics 234

Analytics Retail Storage Monitoring 234

Dynatrace

OCTOBER 14, 2022

This way, it‘s possible to flexibly select what confidential or sensitive information (for example, PII) is hashed or completely removed before it leaves the enterprise premises. OneAgent processes rules precisely in this order, with host scope rules processed before host group and tenant scope rules. Host group.

Storage 236

Storage Government Network Infrastructure 236

Dynatrace

OCTOBER 4, 2022

Teams have introduced workarounds to reduce storage costs. Additionally, efforts such as lowered data retention times, two-tiered storage systems, shaky index management, sampled data, and data pipelines reduce the overall amount of stored data. Stop worrying about log data ingest and storage — start creating value instead.

Analytics 243

Analytics Artificial Intelligence Storage Serverless 243

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. In late 2021, for example, digital forensics was central to combating the Log4Shell vulnerability. Cold storage and rehydration. Cold storage and rehydration.

Analytics 190

Analytics Storage Retail Monitoring 190

DZone

JANUARY 31, 2024

SIEM platforms streamline incident response processes, allowing security teams to respond quickly and effectively to security incidents. For example, in big organizations, the Linux logs may be around 10 billion, and firewall logs may be around five billion per day.

Storage 136

Storage Data Engineering Network Infrastructure 136

Scalegrid

JANUARY 5, 2024

Despite initial investment costs, DBMS presents long-term savings and improved efficiency through automated processes, efficient query optimizations, and scalability, contributing to enhanced decision-making and end-user productivity. It provides tools for organizing and retrieving data efficiently.

Efficiency 147

Efficiency Storage Database Scalability 147

Dynatrace

DECEMBER 5, 2023

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. In the following example, a synthetic monitor is set up for webpage uptime monitoring.

Efficiency 273

Efficiency Architecture Energy Monitoring 273

Dynatrace

JANUARY 11, 2023

In the process, they’re adopting more tools and technologies. These tools also lack IT context—an awareness of the systems and processes responsible for the business data. High storage costs. This combination offers rich data management and analytics on top of low-cost cloud storage. Search constraints.

Analytics 198

Analytics Strategy Storage Technology 198

Dynatrace

OCTOBER 4, 2022

For example, users generate user data, ecommerce sites generate business data, and service portals generate service desk tickets and call volume data. 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 200

Analytics Software Software Storage 200

Scalegrid

JULY 17, 2020

If you store each of the keys as columns, it will result in frequent DML operations – this can be difficult when your data set is large - for example, event tracking, analytics, tags, etc. For example, Stripe transactions. JSON is faster to ingest vs. JSONB – however, if you do any further processing, JSONB will be faster.

Storage 321

Storage Database Efficiency Processing 321

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. Fault-tolerance. Interoperability with Hadoop.

Big Data 154

Big Data Processing Lambda Database 154

The Netflix TechBlog

NOVEMBER 29, 2023

Bitrate versus quality comparison HDR-VMAF is designed to be format-agnostic — it measures the perceptual quality of HDR video signal regardless of its container format, for example, Dolby Vision or HDR10. Shown below are rate versus quality examples for a couple of titles from our HDR catalog. We present two sets. The first set (Fig.

Open Source 252

Open Source Software Engineering Internet Internet 252

Dynatrace

DECEMBER 18, 2023

This covers the infrastructure, processes, and the application stack, including tracing, profiling, and logs. But often, we use additional services and solutions within our environment for backups, storage, networking, and more. Our goal was to filter for metrics that deliver the data we need while minimizing storage costs.

Metrics 186

Metrics Engineering Energy Tuning 186

Dynatrace

MARCH 27, 2024

AWS AppFabric ingests and normalizes audit logs from SaaS applications and delivers them to an Amazon Simple storage service (Amazon S3) bucket in an organization’s AWS account. For example, some SaaS applications include the user’s IP Address and Country on their audit logs. 16) our company users access the internet from.

AWS 252

AWS Analytics Government Monitoring 252

Dynatrace

FEBRUARY 2, 2023

When combined with Dynatrace Grail™, business events gain long-term, cost-effective storage, unaggregated granularity, instant indexless queries, and automatic Smartscape ® topology context. It’s at this point—immediately after processing—where you can extract metrics from your events by defining extraction rules.

Analytics 210

Analytics Metrics DevOps Storage 210

The Netflix TechBlog

OCTOBER 27, 2020

Usually Data scientists and engineers write Extract-Transform-Load (ETL) jobs and pipelines using big data compute technologies, like Spark or Presto , to process this data and periodically compute key information for a member or a video. The processed data is typically stored as data warehouse tables in AWS S3.

Latency 243

Latency Storage Big Data Tuning 243

The Morning Paper

FEBRUARY 20, 2020

Extending relational query processing with ML inference , Karanasos, CIDR’10. … based on interactions with enterprise customers, we expect that storage and inference of ML models will be subject to the same scrutiny and performance requirements of sensitive/mission-critical operational data. An INSERT INTO model.

Processing 72

Processing Hardware Database Azure 72