What we're about

This group is for anyone interested in open source search, logging, analytics & data visualization. We primarily focus on these open source projects — Elasticsearch, Kibana, Logstash, and Beats (www.elastic.co/products) — but we welcome talks on any aspect of data exploration.

We want to hear from you — and so do other meetup members!

Present about your Elastic Stack stories, be it a lightning talk or a 25-45 minute presentation with Q&A. Our Speaker Guide (https://eemrich.gitbooks.io/elastic-user-group-speaker-guidelines/content/) is full of tips on giving a stellar presentation. If you’re interested visit the elastic/call-for-meetups repo (https://github.com/elastic/call-for-meetups).

Host a meetup:

Hosting a meetup at your office, is another way to get more involved with the community. This is a great way to showcase your space (especially if you’re trying to recruit). Your facilities don't need to be fancy — we're looking for a comfortable vibe, a projector, screen, chairs, and a place to serve refreshments. Email

Learn more about Elastic

- Elastic Community: https://www.elastic.co/community

- Monthly Community Newsletter: https://www.elastic.co/community/newsletter

- Discussion Forums: https://discuss.elastic.co/

Code of Conduct

This Meetup community adheres to the Elastic Community Code of Conduct (https://www.elastic.co/community/codeofconduct). Attendance to events run as part of this Meetup group means you agree to be an awesome human and engage by these rules.

Upcoming events (3)

Data Management with Elastic (PART 1)

Needs a location

THIS IS A FREE EVENT - PLEASE FINISH YOUR RSVP IN THE LINK BELOW

https://community.elastic.co/events/details/elastic-pakistan-presents-data-management-with-elastic-part-1/

Hello, Elastic Fantastics!

Time series data tends to grow over time. And while it might be easier to store and manage this data via a single index, it’s often more efficient and cost-effective to store large volumes of time series data across multiple, time-based indices. Multiple indices enable you to move indices containing older, less frequently queried data to less expensive hardware and delete indices when they’re no longer needed, reducing overhead and storage costs.

If you’re collecting a terabyte of data per day, for example, that’s seven terabytes a week. Kept over several years, this easily grows to petabytes of data. Users need a way to manage this exponential storage growth and have the capability to search for everything. Learn how to meet these goals with the help of Elastic.

• Part 1: Index Lifecycle Management (ILM) - [13th October 2021]

ILM automates how you want to manage your indices over time. You control how indices are handled as they age by attaching a lifecycle policy to the index template used to create them. You can update the policy to modify the lifecycle of both new and existing indices.

• Part 2: Data streams - [20th October 2021]

Data streams abstract away — and simplify — some of the complexity that comes with having to manage numerous time-series indices, making features like index lifecycle management (ILM) a breeze to configure and simple to maintain.

• Part 3: Searchable snapshots- [27th October 2021]

Searchable Snapshots allow us to keep low-cost object stores from AWS, Google, Azure, and other object stores always online and available, by making your snapshots directly searchable by Elasticsearch.

Agenda

---

Speaker

Muhammad Sarwar - Elasticsearch (Education Architect)

Muhammad is an Elastic Certified Instructor, with an experience of over 16 years as a Senior Software engineer, Architect and Engineering lead.

Hosts

Aravind Putrevu - Elastic (Developer Advocate)

Aravind works at Elastic as a Developer Advocate and looks after Developer Relations function in India. He has experience working in Cloud Security and Financial Domains. He has interest in Search and Analytics, Security, IoT and Machine Learning. In his free time, he plays around with a RasPi or Arduino :)

Kawnish Panse - Elasticsearch (Community Programs Associate)

---

THIS IS A FREE EVENT - PLEASE FINISH YOUR RSVP IN THE LINK BELOW

https://community.elastic.co/events/details/elastic-pakistan-presents-data-management-with-elastic-part-1/

Data Management with Elastic (PART 2)

Needs a location

THIS IS A FREE EVENT - PLEASE FINISH YOUR RSVP IN THE LINK BELOW

https://community.elastic.co/events/details/elastic-pakistan-presents-data-management-with-elastic-part-2/

Hello, Elastic Fantastics!

Time series data tends to grow over time. And while it might be easier to store and manage this data via a single index, it’s often more efficient and cost-effective to store large volumes of time series data across multiple, time-based indices. Multiple indices enable you to move indices containing older, less frequently queried data to less expensive hardware and delete indices when they’re no longer needed, reducing overhead and storage costs.

If you’re collecting a terabyte of data per day, for example, that’s seven terabytes a week. Kept over several years, this easily grows to petabytes of data. Users need a way to manage this exponential storage growth and have the capability to search for everything. Learn how to meet these goals with the help of Elastic.

• Part 1: Index Lifecycle Management (ILM) - [13th October 2021]

ILM automates how you want to manage your indices over time. You control how indices are handled as they age by attaching a lifecycle policy to the index template used to create them. You can update the policy to modify the lifecycle of both new and existing indices.

• Part 2: Data streams - [20th October 2021]

Data streams abstract away — and simplify — some of the complexity that comes with having to manage numerous time-series indices, making features like index lifecycle management (ILM) a breeze to configure and simple to maintain.

• Part 3: Searchable snapshots- [27th October 2021]

Searchable Snapshots allow us to keep low-cost object stores from AWS, Google, Azure, and other object stores always online and available, by making your snapshots directly searchable by Elasticsearch.

Agenda

---

Speaker

Muhammad Sarwar - Elasticsearch (Education Architect)

Muhammad is an Elastic Certified Instructor, with an experience of over 16 years as a Senior Software engineer, Architect and Engineering lead.

Hosts

Aravind Putrevu - Elastic (Developer Advocate)

Aravind works at Elastic as a Developer Advocate and looks after Developer Relations function in India. He has experience working in Cloud Security and Financial Domains. He has interest in Search and Analytics, Security, IoT and Machine Learning. In his free time, he plays around with a RasPi or Arduino :)

Kawnish Panse - Elasticsearch (Community Programs Associate)

---

THIS IS A FREE EVENT - PLEASE FINISH YOUR RSVP IN THE LINK BELOW

https://community.elastic.co/events/details/elastic-pakistan-presents-data-management-with-elastic-part-2/

Data Management with Elastic (PART 3)

Needs a location

THIS IS A FREE EVENT - PLEASE FINISH YOUR RSVP IN THE LINK BELOW

https://community.elastic.co/events/details/elastic-pakistan-presents-data-management-with-elastic-part-3/

Hello, Elastic Fantastics!

Time series data tends to grow over time. And while it might be easier to store and manage this data via a single index, it’s often more efficient and cost-effective to store large volumes of time series data across multiple, time-based indices. Multiple indices enable you to move indices containing older, less frequently queried data to less expensive hardware and delete indices when they’re no longer needed, reducing overhead and storage costs.

If you’re collecting a terabyte of data per day, for example, that’s seven terabytes a week. Kept over several years, this easily grows to petabytes of data. Users need a way to manage this exponential storage growth and have the capability to search for everything. Learn how to meet these goals with the help of Elastic.

• Part 1: Index Lifecycle Management (ILM) - [13th October 2021]

ILM automates how you want to manage your indices over time. You control how indices are handled as they age by attaching a lifecycle policy to the index template used to create them. You can update the policy to modify the lifecycle of both new and existing indices.

• Part 2: Data streams - [20th October 2021]

Data streams abstract away — and simplify — some of the complexity that comes with having to manage numerous time-series indices, making features like index lifecycle management (ILM) a breeze to configure and simple to maintain.

• Part 3: Searchable snapshots- [27th October 2021]

Searchable Snapshots allow us to keep low-cost object stores from AWS, Google, Azure, and other object stores always online and available, by making your snapshots directly searchable by Elasticsearch.

Agenda

---

Speaker

Muhammad Sarwar - Elasticsearch (Education Architect)

Muhammad is an Elastic Certified Instructor, with an experience of over 16 years as a Senior Software engineer, Architect and Engineering lead.

Hosts

Aravind Putrevu - Elastic (Developer Advocate)

Aravind works at Elastic as a Developer Advocate and looks after Developer Relations function in India. He has experience working in Cloud Security and Financial Domains. He has interest in Search and Analytics, Security, IoT and Machine Learning. In his free time, he plays around with a RasPi or Arduino :)

Kawnish Panse - Elasticsearch (Community Programs Associate)

---

THIS IS A FREE EVENT - PLEASE FINISH YOUR RSVP IN THE LINK BELOW

https://community.elastic.co/events/details/elastic-pakistan-presents-data-management-with-elastic-part-3/

Past events (22)

Photos (144)