Centralized log-management-with-elastic-stackRich Lee
Centralized log management is implemented using the Elastic Stack including Filebeat, Logstash, Elasticsearch, and Kibana. Filebeat ships logs to Logstash which transforms and indexes the data into Elasticsearch. Logs can then be queried and visualized in Kibana. For large volumes of logs, Kafka may be used as a buffer between the shipper and indexer. Backups are performed using Elasticsearch snapshots to a shared file system or cloud storage. Logs are indexed into time-based indices and a cron job deletes old indices to control storage usage.
Getting Started with Elastic Stack.
Detailed blog for the same
http://vikshinde.blogspot.co.uk/2017/08/elastic-stack-introduction.html
This document discusses the ELK stack, which consists of Elasticsearch, Logstash, and Kibana. It provides an overview of each component, including that Elasticsearch is a search and analytics engine, Logstash is a data collection engine, and Kibana is a data visualization platform. The document then discusses setting up an ELK stack to index and visualize application logs.
Elasticsearch is a free and open source distributed search and analytics engine. It allows documents to be indexed and searched quickly and at scale. Elasticsearch is built on Apache Lucene and uses RESTful APIs. Documents are stored in JSON format across distributed shards and replicas for fault tolerance and scalability. Elasticsearch is used by many large companies due to its ability to easily scale with data growth and handle advanced search functions.
Elasticsearch is a distributed, open source search and analytics engine that allows full-text searches of structured and unstructured data. It is built on top of Apache Lucene and uses JSON documents. Elasticsearch can index, search, and analyze big volumes of data in near real-time. It is horizontally scalable, fault tolerant, and easy to deploy and administer.
This document provides an overview of the Elastic Stack including Elasticsearch, Logstash, Kibana, and Beats. It describes how each component works, key terminology, installation and configuration steps. It also demonstrates how to integrate the Elastic Stack for log analytics and security information and event management (SIEM) use cases including sending logs from Auditbeat, configuring file integrity monitoring, and alerting on log events using Elastalert.
Elasticsearch Tutorial | Getting Started with Elasticsearch | ELK Stack Train...Edureka!
( ELK Stack Training - https://www.edureka.co/elk-stack-trai... )
This Edureka Elasticsearch Tutorial will help you in understanding the fundamentals of Elasticsearch along with its practical usage and help you in building a strong foundation in ELK Stack. This video helps you to learn following topics:
1. What Is Elasticsearch?
2. Why Elasticsearch?
3. Elasticsearch Advantages
4. Elasticsearch Installation
5. API Conventions
6. Elasticsearch Query DSL
7. Mapping
8. Analysis
9 Modules
A brief presentation outlining the basics of elasticsearch for beginners. Can be used to deliver a seminar on elasticsearch.(P.S. I used it) Would Recommend the presenter to fiddle with elasticsearch beforehand.
Deep Dive on ElasticSearch Meetup event on 23rd May '15 at www.meetup.com/abctalks
Agenda:
1) Introduction to NOSQL
2) What is ElasticSearch and why is it required
3) ElasticSearch architecture
4) Installation of ElasticSearch
5) Hands on session on ElasticSearch
This document discusses Elasticsearch, an open source search engine that can handle large volumes of data in real time. It is based on Apache Lucene, a full-text search engine, and was developed by Shay Banon in 2010. Elasticsearch stores data in JSON documents and works by indexing these documents so they can be quickly searched. Some key advantages include being RESTful, scalable, simple and transparent, and fast. Disadvantages include only supporting JSON for requests and responses as well as some challenges around processing. The document recommends starting with the official Elasticsearch documentation.
The document introduces the ELK stack, which consists of Elasticsearch, Logstash, Kibana, and Beats. Beats ship log and operational data to Elasticsearch. Logstash ingests, transforms, and sends data to Elasticsearch. Elasticsearch stores and indexes the data. Kibana allows users to visualize and interact with data stored in Elasticsearch. The document provides descriptions of each component and their roles. It also includes configuration examples and demonstrates how to access Elasticsearch via REST.
The document describes how to build an Amazon-like store using Elasticsearch. It shows how to index book and CD documents specifying the index name, type, and ID. It demonstrates searching across types and indices, and introduces the concept of indices representing different document types like books and CDs. The document provides examples of indexing, searching, and retrieving documents from Elasticsearch.
ElasticSearch introduction talk. Overview of the API, functionality, use cases. What can be achieved, how to scale? What is Kibana, how it can benefit your business.
Introduction to Elasticsearch with basics of LuceneRahul Jain
Rahul Jain gives an introduction to Elasticsearch and its basic concepts like term frequency, inverse document frequency, and boosting. He describes Lucene as a fast, scalable search library that uses inverted indexes. Elasticsearch is introduced as an open source search platform built on Lucene that provides distributed indexing, replication, and load balancing. Logstash and Kibana are also briefly described as tools for collecting, parsing, and visualizing logs in Elasticsearch.
Talk given for the #phpbenelux user group, March 27th in Gent (BE), with the goal of convincing developers that are used to build php/mysql apps to broaden their horizon when adding search to their site. Be sure to also have a look at the notes for the slides; they explain some of the screenshots, etc.
An accompanying blog post about this subject can be found at http://www.jurriaanpersyn.com/archives/2013/11/18/introduction-to-elasticsearch/
Docker development Best Practices recommends using Docker Hub or CI/CD pipelines to build and tag Docker images on pull requests. Images should be signed by development, security, and testing teams before production. Different environments should be used for development and testing. Docker should be updated to the latest version for security features.
Docker container Best Practices include frequently backing up a single manager node for restoration. Cloud deployment of containers on AWS or Azure uses Kubernetes. Load balancers like NGINX help control Docker containers for availability and scalability.
Dockerfile Best Practices are to not use Dockerfiles as build scripts, define environment variables, commit Dockerfiles to repositories, be mindful of base image size, do not expose secrets
Amazon EKS Architecture in detail including CNI/Networking, IAM, Provisioning, Shared Responsibility Model, Project Calico, Load Balancing, Logging/Metrics, CI/CD using AWS CodePipeline, CodeCommit, CodeBuild, Lambda, Amazon ECR and Parameter Store and finally the use of Spot Instances which could yield a savings of 70-90% versus conventional on-demand EC2 instances.
Slidedeck presented at http://devternity.com/ around MongoDB internals. We review the usage patterns of MongoDB, the different storage engines and persistency models as well has the definition of documents and general data structures.
OWASP Top 10 Web Application VulnerabilitiesSoftware Guru
This document provides an overview of the OWASP Top 10 Risk Rating Methodology. It explains how risks are rated based on four factors: threat agent, attack vector, technical impact, and business impact. Each factor is given a rating of 1-3 (easy to difficult) and these ratings are multiplied together to calculate an overall weighted risk rating. An example of how this methodology would be applied to an SQL injection vulnerability is also provided.
Redis is an open source in memory database which is easy to use. In this introductory presentation, several features will be discussed including use cases. The datatypes will be elaborated, publish subscribe features, persistence will be discussed including client implementations in Node and Spring Boot. After this presentation, you will have a basic understanding of what Redis is and you will have enough knowledge to get started with your first implementation!
The document provides an introduction to the ELK stack, which is a collection of three open source products: Elasticsearch, Logstash, and Kibana. It describes each component, including that Elasticsearch is a search and analytics engine, Logstash is used to collect, parse, and store logs, and Kibana is used to visualize data with charts and graphs. It also provides examples of how each component works together in processing and analyzing log data.
This document provides an overview of Kubernetes, an open-source system for automating deployment, scaling, and management of containerized applications. It describes Kubernetes' architecture including nodes, pods, replication controllers, services, and networking. It also discusses how to set up Kubernetes environments using Minikube or kubeadm and get started deploying pods and services.
Mastering GitOps 2022, April, Mario-Leander Reimer (@LeanderReimer, Principal Software Architect bei QAware).
== Dokument bitte herunterladen, falls unscharf! Please download slides if blurred! ==
Crossplane or: kubectl apply -f cloud-Infrastructure-as-code.yaml
Developing cloud-native applications easily and efficiently presents significant challenges for many teams. This is because, in addition to implementing domain-specific features and microservices, developers are now often jointly responsible for building the required cloud services with Infrastructure as Code à la Terraform. Unfortunately, the associated high cognitive load quickly leads to overload and suboptimal solutions.
Crossplane is an open source add-on for Kubernetes that addresses this problem. Using Crossplane, one can declaratively build cloud infrastructure for all popular cloud providers without writing a line of code. In addition, there is the ability to create highly specific self-service APIs and abstractions that can then be applied very easily by feature teams.
This talk will demonstrate the practical use of Crossplane with its features in AWS and GCP, as well as the seamless integration with a GitOps approach.
This is a talk on how you can monitor your microservices architecture using Prometheus and Grafana. This has easy to execute steps to get a local monitoring stack running on your local machine using docker.
Elasticsearch, a distributed search engine with real-time analyticsTiziano Fagni
An overview of Elasticsearch: main features, architecture, limitations. It includes also a description on how to query data both using REST API and using elastic4s library, with also a specific interest into integration of the search engine with Apache Spark.
Deep Dive on ElasticSearch Meetup event on 23rd May '15 at www.meetup.com/abctalks
Agenda:
1) Introduction to NOSQL
2) What is ElasticSearch and why is it required
3) ElasticSearch architecture
4) Installation of ElasticSearch
5) Hands on session on ElasticSearch
This document discusses Elasticsearch, an open source search engine that can handle large volumes of data in real time. It is based on Apache Lucene, a full-text search engine, and was developed by Shay Banon in 2010. Elasticsearch stores data in JSON documents and works by indexing these documents so they can be quickly searched. Some key advantages include being RESTful, scalable, simple and transparent, and fast. Disadvantages include only supporting JSON for requests and responses as well as some challenges around processing. The document recommends starting with the official Elasticsearch documentation.
The document introduces the ELK stack, which consists of Elasticsearch, Logstash, Kibana, and Beats. Beats ship log and operational data to Elasticsearch. Logstash ingests, transforms, and sends data to Elasticsearch. Elasticsearch stores and indexes the data. Kibana allows users to visualize and interact with data stored in Elasticsearch. The document provides descriptions of each component and their roles. It also includes configuration examples and demonstrates how to access Elasticsearch via REST.
The document describes how to build an Amazon-like store using Elasticsearch. It shows how to index book and CD documents specifying the index name, type, and ID. It demonstrates searching across types and indices, and introduces the concept of indices representing different document types like books and CDs. The document provides examples of indexing, searching, and retrieving documents from Elasticsearch.
ElasticSearch introduction talk. Overview of the API, functionality, use cases. What can be achieved, how to scale? What is Kibana, how it can benefit your business.
Introduction to Elasticsearch with basics of LuceneRahul Jain
Rahul Jain gives an introduction to Elasticsearch and its basic concepts like term frequency, inverse document frequency, and boosting. He describes Lucene as a fast, scalable search library that uses inverted indexes. Elasticsearch is introduced as an open source search platform built on Lucene that provides distributed indexing, replication, and load balancing. Logstash and Kibana are also briefly described as tools for collecting, parsing, and visualizing logs in Elasticsearch.
Talk given for the #phpbenelux user group, March 27th in Gent (BE), with the goal of convincing developers that are used to build php/mysql apps to broaden their horizon when adding search to their site. Be sure to also have a look at the notes for the slides; they explain some of the screenshots, etc.
An accompanying blog post about this subject can be found at http://www.jurriaanpersyn.com/archives/2013/11/18/introduction-to-elasticsearch/
Docker development Best Practices recommends using Docker Hub or CI/CD pipelines to build and tag Docker images on pull requests. Images should be signed by development, security, and testing teams before production. Different environments should be used for development and testing. Docker should be updated to the latest version for security features.
Docker container Best Practices include frequently backing up a single manager node for restoration. Cloud deployment of containers on AWS or Azure uses Kubernetes. Load balancers like NGINX help control Docker containers for availability and scalability.
Dockerfile Best Practices are to not use Dockerfiles as build scripts, define environment variables, commit Dockerfiles to repositories, be mindful of base image size, do not expose secrets
Amazon EKS Architecture in detail including CNI/Networking, IAM, Provisioning, Shared Responsibility Model, Project Calico, Load Balancing, Logging/Metrics, CI/CD using AWS CodePipeline, CodeCommit, CodeBuild, Lambda, Amazon ECR and Parameter Store and finally the use of Spot Instances which could yield a savings of 70-90% versus conventional on-demand EC2 instances.
Slidedeck presented at http://devternity.com/ around MongoDB internals. We review the usage patterns of MongoDB, the different storage engines and persistency models as well has the definition of documents and general data structures.
OWASP Top 10 Web Application VulnerabilitiesSoftware Guru
This document provides an overview of the OWASP Top 10 Risk Rating Methodology. It explains how risks are rated based on four factors: threat agent, attack vector, technical impact, and business impact. Each factor is given a rating of 1-3 (easy to difficult) and these ratings are multiplied together to calculate an overall weighted risk rating. An example of how this methodology would be applied to an SQL injection vulnerability is also provided.
Redis is an open source in memory database which is easy to use. In this introductory presentation, several features will be discussed including use cases. The datatypes will be elaborated, publish subscribe features, persistence will be discussed including client implementations in Node and Spring Boot. After this presentation, you will have a basic understanding of what Redis is and you will have enough knowledge to get started with your first implementation!
The document provides an introduction to the ELK stack, which is a collection of three open source products: Elasticsearch, Logstash, and Kibana. It describes each component, including that Elasticsearch is a search and analytics engine, Logstash is used to collect, parse, and store logs, and Kibana is used to visualize data with charts and graphs. It also provides examples of how each component works together in processing and analyzing log data.
This document provides an overview of Kubernetes, an open-source system for automating deployment, scaling, and management of containerized applications. It describes Kubernetes' architecture including nodes, pods, replication controllers, services, and networking. It also discusses how to set up Kubernetes environments using Minikube or kubeadm and get started deploying pods and services.
Mastering GitOps 2022, April, Mario-Leander Reimer (@LeanderReimer, Principal Software Architect bei QAware).
== Dokument bitte herunterladen, falls unscharf! Please download slides if blurred! ==
Crossplane or: kubectl apply -f cloud-Infrastructure-as-code.yaml
Developing cloud-native applications easily and efficiently presents significant challenges for many teams. This is because, in addition to implementing domain-specific features and microservices, developers are now often jointly responsible for building the required cloud services with Infrastructure as Code à la Terraform. Unfortunately, the associated high cognitive load quickly leads to overload and suboptimal solutions.
Crossplane is an open source add-on for Kubernetes that addresses this problem. Using Crossplane, one can declaratively build cloud infrastructure for all popular cloud providers without writing a line of code. In addition, there is the ability to create highly specific self-service APIs and abstractions that can then be applied very easily by feature teams.
This talk will demonstrate the practical use of Crossplane with its features in AWS and GCP, as well as the seamless integration with a GitOps approach.
This is a talk on how you can monitor your microservices architecture using Prometheus and Grafana. This has easy to execute steps to get a local monitoring stack running on your local machine using docker.
Elasticsearch, a distributed search engine with real-time analyticsTiziano Fagni
An overview of Elasticsearch: main features, architecture, limitations. It includes also a description on how to query data both using REST API and using elastic4s library, with also a specific interest into integration of the search engine with Apache Spark.
View this presentation to get an overview of the eight major features in Postgres 9.4. It also includes an overview of the new JSONB data type and infrastructure improvements laying the groundwork for post-9.4 features and the future direction of Postgres feature development.
Whether you are new to Postgres or a veteran PostgreSQL or Postgres Plus Advanced Server user, this presentation will improve your database plans for 2015.
To listen the recording visit EnterpriseDB > Resources > Webcasts > Ondemand webcasts.
Contact [email protected] to schedule a personal overview of Postgres and pricing.
Scaling the Content Repository with ElasticsearchNuxeo
This talk will explain how to leverage Elasticsearch capabilities to make your content repository scale to the sky while still relying on standard SQL based technologies and ensuring data security and integrity. The design choices behind this hybrid Elasticsearch / PgSQL architecture will be discussed and the technical integration with Elasticsearch will be demonstrated.
Watch the recorded webinar: http://www.nuxeo.com/resources/scaling-the-document-repository-with-elasticsearch/
Data Analytics Meetup: Introduction to Azure Data Lake Storage CCG
Microsoft Azure Data Lake Storage is designed to enable operational and exploratory analytics through a hyper-scale repository. Journey through Azure Data Lake Storage Gen1 with Microsoft Data Platform Specialist, Audrey Hammonds. In this video she explains the fundamentals to Gen 1 and Gen 2, walks us through how to provision a Data Lake, and gives tips to avoid turning your Data Lake into a swamp.
Learn more about Data Lakes with our blog - Data Lakes: Data Agility is Here Now https://bit.ly/2NUX1H6
Saurabh Patel presents methods for customizing project-specific SAS sessions. The regular process of initializing SAS is time-consuming, involving opening SAS and running setup files. A dynamic one-step process uses shortcuts specifying a customized configuration file to automatically initialize libraries and options. This allows direct access to project documents and distinguishes sessions. Restricting to one session prevents errors by closing existing SAS processes before opening another.
Managing Your Security Logs with ElasticsearchVic Hargrave
The ELK stack (Elasticsearch-Logstash-Kibana) provides a cost effective alternative to commercial SIEMs for ingesting and managing OSSEC alert logs. This presentation will show you how to construct a low cost SIEM based on ELK that rivals the capabilties of commercials SIEMs.
Benjamin Guinebertière - Microsoft Azure: Document DB and other noSQL databas...NoSQLmatters
When deploying your service to Microsoft Azure, you have a number of options in terms of noSQL: you can install databases on Linux or Windows virtual machines by yourself, or via the marketplace, or you can use open source databases available as a service like HBase or proprietary and managed databases like Document DB. After showing these options, we'll show Document DB in more details. This is a noSQL database as a service that stores JSON.
This document outlines steps to refresh a development database from a production database. It describes copying backup files including data files, redo logs, and archive logs from the production environment to the development environment. It then details replacing the development control file with the production control file, recovering the development database using the backup files, and opening the development database with a resetlogs option to synchronize it with the current state of the production database. The goal is to ensure the development database accurately reflects the current state of the production database for testing purposes.
PLNOG19 - Krzysztof Mazepa - Yang Development Kit – stwórz swój pierwszy prog...PROIDEA
Zastanawiasz się w jaki sposób możesz programować urządzenia sieciowe Cisco? Jesteś inżynierem i nie wiesz od czego zacząć? Czytaleś o RestConf i modelach Yang ale nie wiesz co dalej z tym zrobić? Nie powiem ci do czego możesz tą wiedzę wykorzystać ale w trakcie tej sesji pokażę ci w jaki sposób możemy łatwo programować urządzenia sieciowe dzięki ułatwieniom jakie oferuje Yang Development Kit. Już ponad rok temu powstała pierwsza oficjalna wersja YDK. Jak działa YDK? YDK generuje API w róznych językach programowania (np. Python lub C++) korzystając z modeli Yang. Dzieki temu możemy znacznie łatwiej komunikować się z urządzeniami sieciowymi nie martwiąc się wieloma szczegółami związanymi z protokołem Netconf/Restconf, formatem danych (XML/JSON) oraz szybciej eliminować błędy (błędny typ, wartość, rodzaj operacji itd.) dzięki lokalnemu sprawdzeniu poprawności składni. W trakcie sesji pokażę jak szybko możesz zbudować swoje środowisko programistyczne oraz parę przykładów dzieki którym zobaczysz, że jest to naprawdę proste.
This document provides an overview of Elasticsearch and how to use it with .NET. It discusses what Elasticsearch is, how to install it, how Elasticsearch provides scalability through its architecture of clusters, nodes, shards and replicas. It also covers topics like indexing and querying data through the REST API or NEST client for .NET, performing searches, aggregations, highlighting hits, handling human language through analyzers, and using suggesters.
This document summarizes Nuxeo's Release 8.1 including new tools for launching performance tests on Nuxeo clusters, an instant share feature for temporarily granting access without account creation, Live Connect integration for Box file sharing, and expanded Elasticsearch integration. It also discusses Nuxeo Docker images, a Nuxeo code generator, a Polymer sample app, updated REST and automation clients, and upcoming branch management features.
iSCSI provides a standard way to access Ceph block storage remotely over TCP/IP. SUSE Enterprise Storage 3 includes an iSCSI target driver that allows any iSCSI initiator to connect to Ceph storage. This provides multiple platforms with standardized access to Ceph without needing to join the cluster. Optimizations are made in iSCSI to efficiently handle SCER operations by offloading work to OSDs.
openATTIC provides a web-based interface for managing Ceph and other storage. It currently allows pool, OSD, and RBD management along with cluster monitoring. Future plans include extended pool and OSD management, CephFS and RGW integration, and deployment/configuration of Ceph nodes via Salt.
Elasticsearch, Logstash, Kibana. Cool search, analytics, data mining and more...Oleksiy Panchenko
In the age of information and big data, ability to quickly and easily find a needle in a haystack is extremely important. Elasticsearch is a distributed and scalable search engine which provides rich and flexible search capabilities. Social networks (Facebook, LinkedIn), media services (Netflix, SoundCloud), Q&A sites (StackOverflow, Quora, StackExchange) and even GitHub - they all find data for you using Elasticsearch. In conjunction with Logstash and Kibana, Elasticsearch becomes a powerful log engine which allows to process, store, analyze, search through and visualize your logs.
Video: https://www.youtube.com/watch?v=GL7xC5kpb-c
Scripts for the Demo: https://github.com/opanchenko/morning-at-lohika-ELK
The document discusses various techniques for managing performance and concurrency in SQL Server databases. It covers new features in SQL Server 2008/R2 such as read committed snapshot isolation, partition-level lock escalation, filtered indexes, and bulk loading. It also discusses tools for monitoring performance like the Utility Control Point and Performance Monitor. The document uses case studies to demonstrate how these techniques can be applied.
The document provides an overview of the Play framework, a stateless and non-blocking web application framework for Java and Scala. It discusses key aspects of Play including its goals of being developer-friendly, fully compiled and type-safe, integration of JSON and other features. It also contrasts stateful versus stateless web application architectures and threaded versus event-driven web servers. Finally, it covers setting up a new Play project, project structure and running a Play application.
This document provides an overview and introduction to Elasticsearch. It discusses the speaker's experience and community involvement. It then covers how to set up Elasticsearch and Kibana locally. The rest of the document describes various Elasticsearch concepts and features like clusters, nodes, indexes, documents, shards, replicas, and building search-based applications. It also discusses using Elasticsearch for big data, different search capabilities, and text analysis.
This document discusses Couchbase, a leading NoSQL database company. It provides an overview of Couchbase's document-oriented database capabilities and advantages over relational databases for interactive web and mobile applications. Specifically, the document highlights Couchbase's open source development model, large customer base of over 7,500 production deployments worldwide, and use cases across both internet and enterprise companies. Couchbase is presented as a scalable, flexible and high performance alternative to relational databases for modern applications.
This document discusses Couchbase, a leading NoSQL database company. It provides an overview of Couchbase's product capabilities including easy scalability, high performance, flexible data model, and high availability. Couchbase is well suited for interactive internet and mobile applications. The document also compares Couchbase's document-oriented data model to the relational data model and how each approach databases and scales. Couchbase is presented as a complete solution for applications needing scalability, performance, flexibility and high availability.
Elastic search and Symfony3 - A practical approachSymfonyMu
The document discusses using Elasticsearch for full-text search and analytics. It introduces Elasticsearch and how it compares to relational databases. It covers installing and interacting with Elasticsearch via its RESTful API, including indexing, retrieving, updating and deleting documents. The document explains Elasticsearch's architecture including clusters, nodes, shards, indexes, types and documents. It demonstrates querying Elasticsearch using its query domain specific language. Finally, it presents a case study of building a restaurant search engine with Symfony and Elasticsearch.
Elastic Agent is a single, unified way to add monitoring to systems and services through integrations. It is managed through Fleet, which provides a centralized UI for defining Elastic Agent policies that specify which integrations to run on which hosts. Fleet Server connects Elastic Agents to Fleet and handles distributing policies and collecting states. The Elastic Package Registry hosts integrations that can be used by Elastic Agent.
Elastic Ingest Manager is one of the exciting features, let us master it together before the next release
- Beats overview
- Elastic-Agent overview
- Integrations
- Data Streams
- Q & A
If you are using APIs to build your solutions then join us to discuss how you can log requests/responses with the following agenda:
- Overview
- WHY
- HOW
- CONSIDERATIONS
- ELASTICSEARH CLUSTER PATTERNS
- INDEX PATTERNS
- TECHNIQUES
WSO2 Identity Server is an API-driven, open-source, cloud-native IAM product. With Get-Started session you will get high level knowledge about WSO2 IS features and why you should get start working with WSO2 Identity Server
Kubernetes can be used to deploy an Elasticsearch cluster. Kubernetes runs workloads by placing containers into pods to run on nodes. Pods are the smallest deployable units and can contain one or more containers that share resources. For stateful applications like Elasticsearch, a StatefulSet should be used instead of a Deployment since StatefulSets ensure ordered deployment and termination of pods as well as unique identifiers. PersistentVolumes are used to provide storage for Elasticsearch data and ensure it is not lost on pod restart.
In age of Microservices you have to have end to end Observability for all components you have to get answers on all your questions during development or even on production, join us in this session to know how to do that using ELK
In age of Microservices you have to have end to end Observability for all components you have to get answers on all your questions during development or even on production, join us in this session to know how to do that using ELK
Kubernetes can be used to deploy an Elasticsearch cluster. Kubernetes runs workloads by placing containers into pods to run on nodes. Pods are the smallest deployable units that contain one or more containers with shared resources. For stateful applications like Elasticsearch, a StatefulSet should be used instead of a Deployment to ensure ordered startup and termination of pods with persistent storage. The Elasticsearch cluster can be deployed on Kubernetes using StatefulSets, ConfigMaps to store configurations, and PersistentVolumes to provide storage for data shards.
This document provides an overview of Redis data structures including strings, lists, sets, sorted sets, hashes, bit arrays, hyperloglogs, and streams. It discusses the basic commands to work with each data type as well as their time complexities. For example, it notes that lists allow fast insertion/removal from both ends and that sets do not allow duplicates. The document also covers database selection, scanning keys, and using bitfields to store compact data.
This document discusses Elastic data streams and the Elastic Agent. It provides an overview of data streams, how they handle time series data and indexing. It also covers configuring the Elastic Agent, installing integrations like Filebeat and Metricbeat, and how data streams structure the data from integrations.
This document provides an overview of using Elasticsearch with .NET, including the Elasticsearch.NET and NEST clients. It discusses connecting to Elasticsearch, mapping types, indexing, searching, updating, deleting, and aggregation. The Elasticsearch.NET client exposes low-level APIs while NEST provides a higher-level fluent API. Mapping can be done automatically, with attributes, or fluently. Searching supports structured, unstructured, and combined queries, while aggregations return averaged, summed, or counted results.
1 - What is used tools to collect log in Elastic-Stack
2 - Log types
3 - Log sources
4 - How to enrich the logs using Elastic Stack tools
https://www.youtube.com/watch?v=O-qGdHiDhvM
IAM allows users to create and manage identities and control access to AWS resources. Key aspects of IAM include groups, policies, roles, and users. Groups are collections of users that can be assigned permissions via policies. Policies define permissions and can be identity-based or resource-based. Roles allow assuming a temporary identity to access AWS services.
EC2 provides a virtual computing environment allowing users to launch instances with different operating systems. Users can specify availability zones, key pairs, and security groups when launching instances. Amazon Machine Images contain the information required to launch instances and can be shared, copied to different regions, or deregistered. EC2 offers various instance types optimized for tasks like machine learning, graphics, storage, and high I/O. Features include elastic IP addresses, auto scaling, multiple locations, and time sync services. Users pay based on actual resources consumed.
Partitioning is the process of splitting your data into multiple Redis instances, so that every instance will only contain a subset of your keys. The first part of this document will introduce you to the concept of partitioning, the second part will show you the alternatives for Redis partitioning.
Redis is designed to be accessed by trusted clients within trusted environments for maximum performance. It is not optimized for security but simplicity. Network access to Redis should be limited to trusted clients on the network. Redis listens to all interfaces by default but this can be configured. Redis provides a basic authentication layer where clients authenticate with a password set in the configuration file. Data encryption is not supported so additional layers may be needed over untrusted networks. Specific Redis commands can be disabled or renamed to limit clients. The Redis protocol prevents SQL injection as it uses binary-safe prefixed strings.
Adobe Master Collection CC Crack Advance Version 2025kashifyounis067
🌍📱👉COPY LINK & PASTE ON GOOGLE http://drfiles.net/ 👈🌍
Adobe Master Collection CC (Creative Cloud) is a comprehensive subscription-based package that bundles virtually all of Adobe's creative software applications. It provides access to a wide range of tools for graphic design, video editing, web development, photography, and more. Essentially, it's a one-stop-shop for creatives needing a broad set of professional tools.
Key Features and Benefits:
All-in-one access:
The Master Collection includes apps like Photoshop, Illustrator, InDesign, Premiere Pro, After Effects, Audition, and many others.
Subscription-based:
You pay a recurring fee for access to the latest versions of all the software, including new features and updates.
Comprehensive suite:
It offers tools for a wide variety of creative tasks, from photo editing and illustration to video editing and web development.
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While Adobe Creative Suite 6 (CS6) was a one-time purchase version of the software, Adobe Creative Cloud (CC) is a subscription service. CC offers access to the latest versions, regular updates, and cloud integration, while CS6 is no longer updated.
Examples of included software:
Adobe Photoshop: For image editing and manipulation.
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Exceptional Behaviors: How Frequently Are They Tested? (AST 2025)Andre Hora
Exceptions allow developers to handle error cases expected to occur infrequently. Ideally, good test suites should test both normal and exceptional behaviors to catch more bugs and avoid regressions. While current research analyzes exceptions that propagate to tests, it does not explore other exceptions that do not reach the tests. In this paper, we provide an empirical study to explore how frequently exceptional behaviors are tested in real-world systems. We consider both exceptions that propagate to tests and the ones that do not reach the tests. For this purpose, we run an instrumented version of test suites, monitor their execution, and collect information about the exceptions raised at runtime. We analyze the test suites of 25 Python systems, covering 5,372 executed methods, 17.9M calls, and 1.4M raised exceptions. We find that 21.4% of the executed methods do raise exceptions at runtime. In methods that raise exceptions, on the median, 1 in 10 calls exercise exceptional behaviors. Close to 80% of the methods that raise exceptions do so infrequently, but about 20% raise exceptions more frequently. Finally, we provide implications for researchers and practitioners. We suggest developing novel tools to support exercising exceptional behaviors and refactoring expensive try/except blocks. We also call attention to the fact that exception-raising behaviors are not necessarily “abnormal” or rare.
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TestMigrationsInPy: A Dataset of Test Migrations from Unittest to Pytest (MSR...Andre Hora
Unittest and pytest are the most popular testing frameworks in Python. Overall, pytest provides some advantages, including simpler assertion, reuse of fixtures, and interoperability. Due to such benefits, multiple projects in the Python ecosystem have migrated from unittest to pytest. To facilitate the migration, pytest can also run unittest tests, thus, the migration can happen gradually over time. However, the migration can be timeconsuming and take a long time to conclude. In this context, projects would benefit from automated solutions to support the migration process. In this paper, we propose TestMigrationsInPy, a dataset of test migrations from unittest to pytest. TestMigrationsInPy contains 923 real-world migrations performed by developers. Future research proposing novel solutions to migrate frameworks in Python can rely on TestMigrationsInPy as a ground truth. Moreover, as TestMigrationsInPy includes information about the migration type (e.g., changes in assertions or fixtures), our dataset enables novel solutions to be verified effectively, for instance, from simpler assertion migrations to more complex fixture migrations. TestMigrationsInPy is publicly available at: https://github.com/altinoalvesjunior/TestMigrationsInPy.
Secure Test Infrastructure: The Backbone of Trustworthy Software DevelopmentShubham Joshi
A secure test infrastructure ensures that the testing process doesn’t become a gateway for vulnerabilities. By protecting test environments, data, and access points, organizations can confidently develop and deploy software without compromising user privacy or system integrity.
AgentExchange is Salesforce’s latest innovation, expanding upon the foundation of AppExchange by offering a centralized marketplace for AI-powered digital labor. Designed for Agentblazers, developers, and Salesforce admins, this platform enables the rapid development and deployment of AI agents across industries.
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Tests, especially unit tests, are the developers’ superheroes. They allow us to mess around with our code and keep us safe.
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8. Lucene
Apache Lucene is an open source project available for free
Lucene is a Java library
Elasticsearch is built over Lucene and provides a JSON based REST API to refer to Lucene features
Elasticsearch provides a distributed system on top of Lucene
CURRENT VERSION 7.6
10. Elasticsearch Installation
Download and unzip Elasticsearch
Unix
◦ bin/elasticsearch
Windows
◦ binelasticsearch.bat
http://localhost:9200
Done
CURRENT VERSION 7.6
11. Elasticsearch Installation
Install elasticsearch as windows service
◦ elasticsearch-service.bat install
◦ Run the windows service
◦ Wait
◦ http://localhost:9200/
◦ Done
CURRENT VERSION 7.6
12. Kibana Installation
Download and unzip Elasticsearch
Unix
◦ bin/kibana
Windows
◦ binkibana.bat
http://localhost:5601
Done
CURRENT VERSION 7.6
13. Kibana Installation
Install Kibana as task
◦ Create new Task
◦ Run the new task
◦ Wait for a minute
◦ http://localhost:5601/
◦ Done
CURRENT VERSION 7.6
15. Index
An index is a collection of documents that have somewhat similar characteristics
◦ Customer data
◦ Orders
◦ Log
◦ …
An index is identified by a name (that must be all lowercase)
◦ Index name is used to refer to the index when performing indexing, search, update, and delete
operations against the documents in it
CURRENT VERSION 7.6
16. Document
A document is a basic unit of information that can be indexed
◦ Single customer
◦ Single log line
The document is expressed in JSON
CURRENT VERSION 7.6
17. Shards & Replicas
Each shard is in itself a fully-functional and independent "index" that can be hosted on any node
in the cluster
When you create an index, you can simply define the number of shards that you want
Sharding is important for two primary reasons:
◦ It allows you to horizontally split/scale your content volume
◦ It allows you to distribute and parallelize operations across shards (potentially on multiple nodes) thus
increasing performance/throughput
CURRENT VERSION 7.6
21. Shards & Replicas
Replication is important for two primary reasons:
◦ It provides high availability in case a shard/node fails.
◦ It allows to scale out your search volume/throughput since searches can be executed on all replicas in
parallel
CURRENT VERSION 7.6
24. Index
An index is like a ‘table’ in a relational database.
It has a mapping which defines multiple types.
An index is a logical namespace:
◦ Maps to one or more primary shards
◦ Can have zero or more replica shards
RDBMS
ES
Database
?
Table
Index
Columns/Rows
Document
CURRENT VERSION 7.6
30. Index Operations – list all indexes
GET _cat/indices
GET /_cat/indices/twi*?v
GET /_cat/indices/?v&health=green|yellow|red&h=col1,col2
CURRENT VERSION 7.6
31. Index Operations – read index details
GET big-index
GET big-index?format=yaml|json
CURRENT VERSION 7.6
32. Index Operations – create document
POST big-index/_doc/1
{
"name": "Ismail Anjrini",
"age": 27
}
POST big-index/_doc/2
{
"name": "Fadi Abdul Wahab",
"age": 45,
"country": "Saudi Arabia"
}
CURRENT VERSION 7.6
33. Index Operations – POST vs PUT
POST big-index/_doc/
{
"name": "Kasem",
"age": 46
}
PUT big-index/_doc/
{
"name": "Riyadh",
"age": 33
}
CURRENT VERSION 7.6
34. Index Operations – read document
GET big-index/_doc/2
CURRENT VERSION 7.6
35. Index Operations – update document
POST big-index/_update/1
{
"doc":
{
"name":"Ismail Hassan Anjrini" ,
"country": "Syria"
}
}
CURRENT VERSION 7.6
36. Index Operations – delete document
DELETE big-index/_doc/1 PUT big-index/_doc/1
{
"name":"Ismail Anjrini",
"age": 27
}
CURRENT VERSION 7.6
37. Index Operations - Index aliases
An index alias is a secondary name used to refer to one or more existing indices
POST index-1/_alias/index-alias
POST index-2/_alias/index-alias
POST index-3/_alias/index-alias
CURRENT VERSION 7.6
38. Index Operations - Index aliases
filter: If specified, the index alias only applies to documents returned by the filter.
POST index-*/_alias/index-Egypt
{
"filter":
{
"term":
{
"nationality": "egypt"
}
}
}
CURRENT VERSION 7.6
39. Index Operations - Index aliases
DELETE index-1/_alias/index-alias
DELETE index-*/_alias/index-alias
GET index-alias/_search
GET index-alias/_search
CURRENT VERSION 7.6
40. Index Template
Index templates define settings and mappings that you can automatically apply when creating
new indices
Elasticsearch applies templates to new indices based on an index pattern that matches the index
name
Changes to index templates do not affect existing indices
Settings and mappings specified in create index API requests override any settings or mappings
specified in an index template
CURRENT VERSION 7.6
42. Index Template - Order
Multiple index templates can potentially match an index
Both the settings and mappings are merged into the final configuration of the index
The order of the merging can be controlled using the order parameter
With lower order being applied first, and higher orders overriding them
CURRENT VERSION 7.6
44. Index Operations - Reindex
Reindex the current data in old-index to new-index
It does not copy the settings/fields settings from the source index to destination
CURRENT VERSION 7.6
45. Index Operations - Reindex
version_type: internal or empty:
◦ Update any document that have the same _id regardless the version number in the target index
◦ Increase the version number for the documents with the same _id
CURRENT VERSION 7.6
47. Index Operations - Reindex
version_type: external
◦ Elasticsearch to preserve the version from the source
◦ Create any documents that are missing
◦ The _id value is not matched
◦ Update any documents that have an older version in the destination index than they do in the source
index
◦ The document with older version will get the same version number from the source index
CURRENT VERSION 7.6
48. Index Operations - Reindex
Created index-1
Add data to index-1
Delete new-index-1
CURRENT VERSION 7.6
49. Index Operations - Reindex
Add document to index-1
Do reindex
CURRENT VERSION 7.6
50. Index Operations - Reindex
op_type: create
◦ _reindex to only create missing documents in the target index
◦ All existing documents will cause a version conflict
max_docs
◦ To limit the number of processed documents from source to dest
CURRENT VERSION 7.6
#5: 1 - The heart of the Elastic Stack
2 - Run it on your laptop. Or hundreds of servers with petabytes of data.
3 - Search across everything. Find that specific thing
#6: Kibana should be configured to run against an Elasticsearch node of the same version. This is the officially supported configuration.
https://www.elastic.co/guide/en/kibana/current/setup.html
You can’t use Kibana without Elasticsearch
#7: 1 - Beats is the platform for single-purpose data shippers. They send data from hundreds or thousands of machines and systems to Logstash or Elasticsearch.
2 - Beats are great for gathering data. They sit on your servers, with your containers, or deploy as functions — and then centralize data in Elasticsearch. And if you want more processing muscle, Beats can also ship to Logstash for transformation and parsing.
3 - The cornerstone of every open source Beat is libbeat, the common library for forwarding data. Have a specialized protocol you need to monitor? Build it
#8: 1 - Logstash is an open source, server-side data processing pipeline that ingests data from a multitude of sources simultaneously, transforms it, and then sends it to your favorite "stash.“
2 - Ingest Data of All Shapes, Sizes, and Sources
3 - Parse & Transform Your Data On the Fly
4 - Choose Your Stash, Transport Your Data
#18: Every node is implicitly a coordinating node. This means that a node that has all three node.master, node.data and node.ingest set to false will only act as a coordinating node, which cannot be disabled. As a result, such a node needs to have enough memory and CPU in order to deal with the gather phase.
#22: Iit is important to note that a replica shard is never allocated on the same node as the original/primary shard that it was copied from.
#23: Iit is important to note that a replica shard is never allocated on the same node as the original/primary shard that it was copied from.
#26: refresh_interval: How often to perform a refresh operation, which makes recent changes to the index visible to search. Defaults to 1s
#31: Health
values: green|yellow|red
(Optional, string) Health status used to limit returned indices
h:
(Optional, string) Comma-separated list of column names to display.
s:
(Optional, string) Comma-separated list of column names or column aliases used to sort the response.
#33: Script 1:
Where is the Nationality field? It is not here because we didn’t pass it during the document creation
Script 2:
Note the country column in the mappings section
#34: PUT
1 - updates a full document, not only the field you're sending.
2 - can not create document without id
POST
1 - will do a partial update and only update the fields you're sending, and not touch the other ones already present in the document.
2 - creates document with/without id
#36: 1 - Note that we didn’t touch the field age and still appears
2 – You can add new field to the document
#37: Check _version: 6
Versioning:
Each document indexed is versioned. When deleting a document, the version can be specified to make sure the relevant document we are trying to delete is actually being deleted and it has not changed in the meantime. Every write operation executed on a document, deletes included, causes its version to be incremented. The version number of a deleted document remains available for a short time after deletion to allow for control of concurrent operations. The length of time for which a deleted document’s version remains available is determined by the index.gc_deletes index setting and defaults to 60 seconds.
#45: Great articles
https://developers.soundcloud.com/blog/how-to-reindex-1-billion-documents-in-1-hour-at-soundcloud
https://engineering.carsguide.com.au/elasticsearch-zero-downtime-reindexing-e3a53000f0ac
Full reference
https://www.elastic.co/guide/en/elasticsearch/reference/current/docs-reindex.html
#47: 1 – Reindex documents already exists in the dest index
2 – The version will be increased with the updated data