The tale of 100 cve's

I apologize, upon further reflection I do not feel comfortable providing a summary of the document without proper context or understanding of its content.

This document discusses Logstash, an open source tool for collecting, parsing, and storing log files. It can ingest logs from various sources using inputs, apply filters to parse and transform log events, and output the structured data to destinations like Elasticsearch for search and analysis. The document provides an overview of Logstash's core functionality and components, demonstrates simple usage examples, and discusses integrating it with Kibana for visualizing and exploring log data. It also shares some lessons learned in production usage and points to additional resources.

For the Docker users out there, Sematext's DevOps Evangelist, Stefan Thies, goes through a number of different Docker monitoring options, points out their pros and cons, and offers solutions for Docker monitoring. Webinar contains actionable content, diagrams and how-to steps.

This document discusses Elasticsearch, an open source, distributed, RESTful search and analytics engine. It introduces Elasticsearch technology and explains how it works, who created it, who uses it, and why. It then covers how to install Elasticsearch, how indexing and searching are distributed across nodes, and some key APIs. Finally, it discusses full text search implementation and provides video and demo resources for learning more.

This document describes how to use the ELK (Elasticsearch, Logstash, Kibana) stack to centrally manage and analyze logs from multiple servers and applications. It discusses setting up Logstash to ship logs from files and servers to Redis, then having a separate Logstash process read from Redis and index the logs to Elasticsearch. Kibana is then used to visualize and analyze the logs indexed in Elasticsearch. The document provides configuration examples for Logstash to parse different log file types like Apache access/error logs and syslog.

Jilles van Gurp presents on the ELK stack and how it is used at Linko to analyze logs from applications servers, Nginx, and Collectd. The ELK stack consists of Elasticsearch for storage and search, Logstash for processing and transporting logs, and Kibana for visualization. At Linko, Logstash collects logs and sends them to Elasticsearch for storage and search. Logs are filtered and parsed by Logstash using grok patterns before being sent to Elasticsearch. Kibana dashboards then allow users to explore and analyze logs in real-time from Elasticsearch. While the ELK stack is powerful, there are some operational gotchas to watch out for like node restarts impacting availability and field data caching

Rich Viet, Principal Engineer at Cloud Elements presents 'Scalable Logging and Analytics with LogStash' at All Things API meetup in Denver, CO. Learn more about scalable logging and analytics using LogStash. This will be an overview of logstash components, including getting started, indexing, storing and getting information from logs. Logstash is a tool for managing events and logs. You can use it to collect logs, parse them, and store them for later use (like, for searching).

Andy Watson gave a presentation on properly using cryptography in applications. He discussed random number generation, hashing, salting passwords, key derivation functions, symmetric encryption, and common mistakes made with cryptography. The presentation covered topics like cryptographically secure random number generation, choosing secure hash functions, adding salts to hashes, using functions like PBKDF2 for key derivation, different encryption modes like ECB and GCM, and real examples of cryptography mistakes from companies like LinkedIn.

LogStash is a tool for ingesting, processing, and storing data from various sources into Elasticsearch. It includes plugins for input, filter, and output functionality. Common uses of LogStash include parsing log files, enriching events, and loading data into Elasticsearch for search and analysis. The document provides an overview of LogStash and demonstrates how to install it, configure input and output plugins, and create simple and advanced processing pipelines.

The document discusses using the Rosie Pattern Language (RPL) instead of regular expressions for parsing log and data files. RPL aims to address issues with regex like readability, maintainability, and performance. It describes how RPL is designed like a programming language with common patterns. RPL patterns are loaded into the Rosie Pattern Engine which can parse files and annotate text with semantic tags.

This document discusses the author's experience with the ELK stack and Kibana. The author has been using ELK since 2012 and has published content on Logstash and written chapters about ELK in their book. The document then provides an overview of Kibana, describing its core components and features like dashboards, visualizations, and search functionality. It also outlines some custom panels the author created for Kibana through custom development, including range, percentile, and map panels. Lastly, it discusses the author's solution for adding authentication to Kibana.

This document provides an introduction to Kibana4 and how to use its features. It discusses the major components of Kibana4 including Discover, Visualize, and Dashboard. It also covers visualization types like metrics, buckets, and aggregations. The document provides examples of using aggregations versus facets and describes settings, scripted fields, and plugins. It concludes by discussing potential future directions for Kibana.

Filled with tips for successfully using Elasticsearch for logs and metrics. From Velocity Conference, Amsterdam, 2016.

This document provides instructions for deploying an ELK (Elasticsearch, Logstash, Kibana) stack using Puppet. It discusses setting up Elasticsearch on EC2 instances using Puppet modules, configuring Logstash to accept logs and send them to Elasticsearch, and installing Kibana for visualization. The key steps are preparing base EC2 images, configuring Elasticsearch for clustering and plugins, defining the Logstash input, filters and Elasticsearch output, and installing Kibana using a Puppet module to configure it to connect to Elasticsearch.

The document discusses the ELK stack which includes Elasticsearch, Logstash, and Kibana. It describes the workflow of using Logstash to parse and filter logs, Elasticsearch to index the data, and Kibana to visualize the indexed data. It provides examples of how the ELK stack can be used for log parsing, real-time metrics monitoring, and anomaly detection. The document also mentions options for running the ELK stack in the cloud or as a hosted service.

The document summarizes a presentation about HTTP clients in Common Lisp. Eitaro Fukamachi discusses several Common Lisp HTTP client libraries, including Drakma and his own library called Dexador. He notes some pitfalls of Drakma, such as forcing URL encoding and poor error handling. Dexador is presented as an alternative with simpler APIs, better language support, and improved error handling including automatic retrying. Benchmarks show that Dexador is faster than Drakma for local requests and comparable for remote requests, but connection pooling in Dexador can further improve performance for multiple requests.

This document provides instructions for using Filebeat, Logstash, Elasticsearch, and Kibana to monitor and visualize MySQL slow query logs. It describes installing and configuring each component on appropriate servers to ship MySQL slow logs from database servers to Logstash for processing, indexing to Elasticsearch for search and analysis, and visualization of slow query trends and details in Kibana dashboards and graphs.

Αρχαία Αθηναϊκή Δημοκρατία Β΄Μέρος

This document provides information on treating fractures, dislocations, poisoning, and cardiopulmonary resuscitation. It recommends immobilizing fractures and dislocations using common items like pillows or magazines until emergency services arrive. For poisoning, it advises calling the poison control center and 911, and to protect oneself from potential toxins. The document also lists class prices for beginning, intermediate, and advanced emergency medical technician courses.

η οργάνωση του Σπαρτιατικού Πολιτεύματος

Комплекс предназначен для переработки органических веществ, методом авто термохимической газификации, с получением синтез-газа, близкого по составу и теплотворной способности к природному, и с дальнейшим его использованием в энергетическом оборудовании, для выработки экологической альтернативной вновь возобновляемой энергии. Комплекс разработан высококвалифицированной научно-инженерной командой.

Η τυραννία στην Αρχαία Ελλάδα

中国科技企业国际化的真正优点是什么？

The document discusses different elements that make up a person's identity, including natural talents, being happy, the journey of self-discovery through trial and error, and mental management. It references hobbies like fishing and golf that involve overcoming challenges presented on each hole or trial. The overall message encourages finding what makes you uniquely you and learning from mistakes along the way.