Ana-Maria Calin [InfluxData] | Migrating from OSS to InfluxDB Cloud | InfluxDays NA 2021

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This session demonstrates running InfluxDB OSS on a self-hosted cloud platform on Kubernetes and the process of migrating from OSS to the Usage-Based InfluxDB Cloud Platform as well as showcasing the additional features of InfluxDB Cloud including cost benefits of running the same data set on Usage-Based instead of OSS (if there are any).

Technologie

Ana Calin | Senior Software Engineer,
Deployments Team, InﬂuxData
27.10.2021
The who, the why and the what of
migrating your data.
Migrating from OSS
to InfluxDB Cloud

© 2021 InﬂuxData Inc. All Rights Reserved.
© 2021 InﬂuxData Inc. All Rights Reserved.
Ana Calin
Photo Goes Here
Software Engineer @ InﬂuxData
@AnaMariaCalin
@calinah

© 2021 InﬂuxData Inc. All Rights Reserved.
Content
Should I stay or should I go?
My InfluxDB OSS setup
Steps to consider
Demo time
Resources

© 2021 InﬂuxData Inc. All Rights Reserved.
© 2021 InﬂuxData Inc. All Rights Reserved.

© 2021 InﬂuxData Inc. All Rights Reserved.
InfluxDB CLoud

© 2021 InﬂuxData Inc. All Rights Reserved.
© 2021 InﬂuxData Inc. All Rights Reserved.
Deeper insights
Multi-Region & Multi-Cloud
Interoperability across systems
Elastic services
InﬂuxDB Cloud

© 2021 InﬂuxData Inc. All Rights Reserved.
My InﬂuxDB OSS setup

© 2021 InﬂuxData Inc. All Rights Reserved.
Influxdb CLoud
# Installs influxdb2 chart from github.com/influxdata/helm-charts/
helm upgrade --install influxdays --namespace influxdays
influxdata/influxdb2 --values
~/influxdays-demo/influxdb2_values.yaml
# Installs telegraf chart from github.com/influxdata/helm-charts/
helm upgrade --install telegraf --namespace influxdays
influxdata/telegraf --values
~/influxdays-demo/telegraf_values.yaml

© 2021 InﬂuxData Inc. All Rights Reserved.
~|⇒ kubectl get all -n influxdays
NAME READY STATUS RESTARTS AGE
pod/influxdays-influxdb2-0 1/1 Running 0 28h
pod/telegraf-56798579c7-b4nfj 1/1 Running 0 21h
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
service/influxdays-influxdb2 ClusterIP 10.126.77.243 <none> 80/TCP 28h
service/telegraf ClusterIP 10.126.6.166 <none> 8125/UDP 21h
NAME READY UP-TO-DATE AVAILABLE AGE
deployment.apps/telegraf 1/1 1 1 21h
NAME DESIRED CURRENT READY AGE
replicaset.apps/telegraf-56798579c7 1 1 1 21h
NAME READY AGE
statefulset.apps/influxdays-influxdb2 1/1 28h

© 2021 InﬂuxData Inc. All Rights Reserved.
Before migrating

© 2021 InﬂuxData Inc. All Rights Reserved.
© 2021 InﬂuxData Inc. All Rights Reserved.
Prerequisites for migration
• an InfluxDB Cloud account with an `org_id` and bucket
name - https://cloud2.influxdata.com/signup
• a write token
• quick writes headroom
• headroom for the cardinality you are adding
• a place to hold the LP data x 2 - S3 or GCS or similar

© 2021 InﬂuxData Inc. All Rights Reserved.
© 2021 InﬂuxData Inc. All Rights Reserved.
Influxdays Demo

© 2021 InﬂuxData Inc. All Rights Reserved.
© 2021 InﬂuxData Inc. All Rights Reserved.
Resources
https:/
/cloud2.inﬂuxdata.com/signup
https:/
/github.com/calinah/inﬂuxdays-demo
https:/
/docs.inﬂuxdata.com/inﬂuxdb/v2.0/ref
erence/cli/inﬂuxd/inspect/export-lp/
https:/
/docs.inﬂuxdata.com/inﬂuxdb/v2.0/ref
erence/sample-data/#noaa-ndbc-data

© 2021 InﬂuxData Inc. All Rights Reserved.
Thank You

© 2021 InﬂuxData Inc. All Rights Reserved.
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Are you considering replacing your legacy data historian and moving your OT data to the cloud? Join this technical webinar to learn how to adopt InfluxDB and IO Base - a digital platform used to improve operational efficiencies! Teréga Solutions are the creators of digital solutions used to improve energy efficiencies and to address decarbonization challenges. Their network includes 5,000+ km of gas pipelines within France; they aim to help France attain carbon neutrality by 2050. With these impressive goals in mind, Teréga has created IO-Base — the digital platform to improve industrial performance, and increase profitability. Creating digital twins for their clients allows them to collect data from all production sites and view it in real time, from anywhere and at any time. Discover how Teréga uses InfluxDB, Docker, and AWS to monitor its gas and hydrogen pipeline infrastructure. They chose to replace their legacy data historian with InfluxDB — the purpose built time series database. They are collecting more than 100K different metrics at various frequencies — some are collected every 5 seconds to only every 1-2 minutes. THey have reduced overall IT spend by 50% and collect 2x the amount of data at 20x frequency! By using various industrial protocols (Modbus, OPC-UA, etc.), Teréga improved output, reduced the TCO, and is now able to create added-value services: forecast, monitoring, predictive maintenance. Join this webinar as Thomas Delquié dives into: Teréga's approach to modernizing fossil fuel pipelines IT systems while improving yields and safety Their centralized methodology to collecting sensor, hardware, and network metrics The importance of time series data and why they chose InfluxDB

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FlowForge enables organizations to reliably deliver Node-RED applications in a continuous, collaborative, and secure manner. Node-RED is the popular, low-code programming solution that makes it easy to connect different services using a visual programming environment. InfluxData is the creator of InfluxDB, the purpose-built time series database run by developers at scale and in any environment in the cloud, on-premises, or at the edge. Jump-start monitoring your industrial IoT devices and discover how to build an edge-to-cloud solution with the MING stack. The MING stack includes Mosquitto/MQTT, InfluxDB, Node-RED, and Grafana. This solution can be used to improve fleet management, enable predictive maintenance of industrial machines and power generation equipment (i.e. turbines and generators) and increase safety practices (i.e. buildings, construction sites). Join this webinar to learn best practices from industrial IoT SME's. In this webinar, Robert Marcer and Jay Clifford dive into: Best practices for monitoring sensor data collected by everyone — from the edge to the factory Tips and tricks for using Node-RED and InfluxDB together Demo — see Node-RED and InfluxDB live

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Rust is a systems programming language designed for high performance, type safety, and concurrency. According to Stack Overflow’s annual survey in 2022, Rust is the most loved language with 87% of developers saying they want to continue using it. The same survey also reported that nearly 20% of developers aren’t currently using Rust, but want to start developing using it. Ockam’s suite of programming libraries, command line tools, and managed cloud services enable developers to orchestrate end-to-end encryption. InfluxDB is the purpose-built time series database developed to handle time series data for IoT, monitoring, and real-time analytics. Ockam was originally developed using C, and InfluxDB was originally written using Go; both solutions have been completely rewritten in Rust. Discover why two founders decided to rewrite their developer tools using Rust, and gain insight into the strategy beforehand and the entire process. Join this live panel as Mrinal Wadhwa and Paul Dix dive into: Their approach to rewriting a project in Rust How to build and train engineering teams Tips and tricks learned along the way - pitfalls to look out for! Join this webinar as there will be a live discussion with Q&A

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InfluxData is excited to announce the general availability of InfluxDB Cloud Dedicated! It is a fully managed time series database service running on cloud infrastructure resources that are dedicated to a single tenant. With this new offering, we’re excited to provide our customers with additional security options, and more custom configuration options to best suit customers’ workload requirements. Join this webinar to learn more about InfluxDB Cloud, and the new dedicated database service offering! In this webinar, Balaji Palani and Gary Fowler will dive into: Key features of the new InfluxDB Cloud Dedicated solution Use cases for using the newest version of the purpose-built time series database Live demo During this 1-hour technical webinar, you’ll also get a chance to ask your questions live.

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Many developers and DevOps engineers have become aware of using their observability data to gain greater insights into their infrastructure systems. InfluxDB is the purpose-built time series database used to collect metrics and gain observability into apps, servers, containers, and networks. Developers use InfluxDB to improve the quality and efficiency of their CI/CD pipelines. Start using InfluxDB to aggregate infrastructure and application performance monitoring metrics to enable better anomaly detection, root-cause analysis, and alerting. This session will demonstrate how to record metrics, logs, and traces with one library — OpenTelemetry — and store them in one open source time series database — InfluxDB. Zoe will demonstrate how easy it is to set up the OpenTelemetry Operator for Kubernetes and to store and analyze your data in InfluxDB.

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American Metal Processing Company ("AMP") is the US' largest commercial rotary heat treat facility with customers in the automotive, construction, military, and agriculture industries. They use their atmosphere-protected rotary retort furnaces to provide their clients with three primary hardening services: neutral hardening (quench and temper), carburizing, and carbonitriding. This furnace style ensures consistent, uniform heat treatment process vs. traditional batch-or-belt-style furnaces; excels at processing high volumes of smaller parts with tight tolerances; and improves the strength and toughness of plain carbon steels. Discover why AMP’s use of Telegraf, InfluxDB, Node-RED, and Grafana allows them to gain 24/7 insights into their plant operations and metallurgical results. Learn how they use time-stamped data to gain accurate metrics about their consumables usage, furnace profiles, and machine status. Join this webinar as Grant Pinkos dives into: American Metal Processing's approach to heat treating in a digitized environment through connected systems Their approach to collecting and measuring sensor data to enable predictive maintenance and improve product quality Why they need a time series database for managing and analyzing vast amounts of time-stamped data

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Delft University is the oldest and largest technical university in the Netherlands with 25,000+ students. Since 1999, they have had a team of students (undergraduate and graduate) designing, building, and racing cars, as part of the Formula Student worldwide competition. The competition has grown to include teams from 1K+ universities in 20+ countries. Students are responsible for all aspects of car manufacturing (research, construction, testing, developing, marketing, management, and fundraising). Delft University's team includes 90 students across disciplines. Discover how Delft University's team uses Marple and InfluxDB to collect telemetry and sensor metrics while they develop, test, and race their electrics cars. They collect sensor data about their EV's control systems using a time series platform. During races, they are collecting IoT data about their batteries, accelerometer, gyroscope, tires, etc. The engineers are able to share important car stats during races which help the drivers tweak their driving decisions — all with the goal of winning. After races, the entire team are able to analyze data in Marple to understand what to do better next time. By using Marple + InfluxDB, their team are able to collect, share and analyze high frequency car data used to make their car faster at competitions. Join this webinar as Robbin Baauw and Nero Vanbiervliet dive into: Marple's approach to empowering engineers to organize, analyze, and visualize their data Delft University's collaborative methodology to building and racing their Formula-style race car How InfluxDB is crucial to their collaborative engineering and racing process

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InfluxData

InfluxData is excited to announce the general availability of InfluxDB Cloud's new storage engine! It is a cloud-native, real-time, columnar database optimized for time series data. InfluxDB's rebuilt core was coded in Rust and sits on top of Apache Arrow and DataFusion. InfluxData's team picked Apache Parquet as the persistent format. In this webinar, Paul Dix and Balaji Palani will demonstrate key product features including the removal of cardinality limits! They will dive into: The next phase of the InfluxDB platform How using Apache Arrow's ecosystem has improved InfluxDB's performance and scalability Key features of InfluxDB Cloud's new core — including SQL native support

Introducing InfluxDB’s New Time Series Database Storage Engine

InfluxData

balena.io helps companies develop, deploy, update, and manage IoT devices. By using Linux containers and other cloud technologies, balena enables teams to quickly and easily build fleets of connected devices. Developers are able to use containers with the language of choice and pull IoT sensor data from 70+ different single board computers into balenaCloud. Discover how to use balena.io to automate your InfluxDB deployments at the edge! During this one-hour session, experts from balena and InfluxData will demonstrate how to build and deploy your own air quality IoT solution. You will learn: The fundamentals of IoT sensor deployment and management using balena. How to use a time series platform to collect and visualize metrics from edge devices. Tips and tricks to using balenaCloud to automate InfluxDB deployments and Telegraf configurations. How to use InfluxDB's Edge Data Replication feature to collect sensor data and push it to InfluxDB Cloud for analysis. No coding experience required, just a curiosity to start your own IoT adventure.

Start Automating InfluxDB Deployments at the Edge with balena

InfluxData

Learn more about InfluxDB’s new storage engine! The team developed a cloud-native, real-time, columnar database optimized for time series data. We built it all in Rust and it sits on top of Apache Arrow and DataFusion. We chose Apache Parquet as the persistent format, which is an open source columnar data file format. This new storage engine provides InfluxDB Cloud users with new functionality, including the removal of cardinality limits, so developers can bring in massive amounts of time series data at scale. In this webinar, Anais Dotis-Georgiou will dive into: Requirements for rebuilding InfluxDB’s core Key product features and timeline How Apache Arrow’s ecosystem is used to meet those requirements Stick around for a demo and live Q&A

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RudderStack — the creators of the leading open source Customer Data Platform (CDP) — needed a scalable way to collect and store metrics related to customer events and processing times (down to the nanosecond). They provide their clients with data pipelines that simplify data collection from applications, websites, and SaaS platforms. RudderStack's solution enables clients to stream customer data in real time — they quickly deploy flexible data pipelines that send the data to the customer's entire stack without engineering headaches. Customers are able to stream data from any tool using their 16+ SDK's, and they are able to transform the data in-transit using JavaScript or Python. How does RudderStack use a time series platform to provide their customers with real-time analytics? Join this webinar as Ryan McCrary dives into: RudderStack's approach to streamlining data pipelines with their 180+ out-of-the-box integrations Their data architecture including Kapacitor for alerting and Grafana for customized dashboards Why using InfluxDB was crucial for them for fast data collection and providing single-sources of truths for their customers

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Enterprise Knowledge’s Urmi Majumder, Principal Data Architecture Consultant, and Fernando Aguilar Islas, Senior Data Science Consultant, presented "Driving Behavioral Change for Information Management through Data-Driven Green Strategy" on March 27, 2024 at Enterprise Data World (EDW) in Orlando, Florida. In this presentation, Urmi and Fernando discussed a case study describing how the information management division in a large supply chain organization drove user behavior change through awareness of the carbon footprint of their duplicated and near-duplicated content, identified via advanced data analytics. Check out their presentation to gain valuable perspectives on utilizing data-driven strategies to influence positive behavioral shifts and support sustainability initiatives within your organization. In this session, participants gained answers to the following questions: - What is a Green Information Management (IM) Strategy, and why should you have one? - How can Artificial Intelligence (AI) and Machine Learning (ML) support your Green IM Strategy through content deduplication? - How can an organization use insights into their data to influence employee behavior for IM? - How can you reap additional benefits from content reduction that go beyond Green IM?

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With more memory available, system performance of three Dell devices increased, which can translate to a better user experience Conclusion When your system has plenty of RAM to meet your needs, you can efficiently access the applications and data you need to finish projects and to-do lists without sacrificing time and focus. Our test results show that with more memory available, three Dell PCs delivered better performance and took less time to complete the Procyon Office Productivity benchmark. These advantages translate to users being able to complete workflows more quickly and multitask more easily. Whether you need the mobility of the Latitude 5440, the creative capabilities of the Precision 3470, or the high performance of the OptiPlex Tower Plus 7010, configuring your system with more RAM can help keep processes running smoothly, enabling you to do more without compromising performance.

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Created by Mozilla Research in 2012 and now part of Linux Foundation Europe, the Servo project is an experimental rendering engine written in Rust. It combines memory safety and concurrency to create an independent, modular, and embeddable rendering engine that adheres to web standards. Stewardship of Servo moved from Mozilla Research to the Linux Foundation in 2020, where its mission remains unchanged. After some slow years, in 2023 there has been renewed activity on the project, with a roadmap now focused on improving the engine’s CSS 2 conformance, exploring Android support, and making Servo a practical embeddable rendering engine. In this presentation, Rakhi Sharma reviews the status of the project, our recent developments in 2023, our collaboration with Tauri to make Servo an easy-to-use embeddable rendering engine, and our plans for the future to make Servo an alternative web rendering engine for the embedded devices industry. (c) Embedded Open Source Summit 2024 April 16-18, 2024 Seattle, Washington (US) https://events.linuxfoundation.org/embedded-open-source-summit/ https://ossna2024.sched.com/event/1aBNF/a-year-of-servo-reboot-where-are-we-now-rakhi-sharma-igalia

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What are drone anti-jamming systems? The drone anti-jamming systems and anti-spoof technology protect against interference, jamming, and spoofing of the UAVs. To protect their security, countries are beginning to research drone anti-jamming systems, also known as drone strike weapons. The anti-jam and anti-spoof technology protects against interference, jamming and spoofing. A drone strike weapon is a drone attack weapon that can attack and destroy enemy drones. So what is so unique about this amazing system?

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As privacy and data protection regulations evolve rapidly, organizations operating in multiple jurisdictions face mounting challenges to ensure compliance and safeguard customer data. With state-specific privacy laws coming up in multiple states this year, it is essential to understand what their unique data protection regulations will require clearly. How will data privacy evolve in the US in 2024? How to stay compliant? Our panellists will guide you through the intricacies of these states' specific data privacy laws, clarifying complex legal frameworks and compliance requirements. This webinar will review: - The essential aspects of each state's privacy landscape and the latest updates - Common compliance challenges faced by organizations operating in multiple states and best practices to achieve regulatory adherence - Valuable insights into potential changes to existing regulations and prepare your organization for the evolving landscape

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Abhishek Deb(1), Mr Abdul Kalam(2) M. Des (UX) , School of Design, DIT University , Dehradun. This paper explores the future potential of AI-enabled smartphone processors, aiming to investigate the advancements, capabilities, and implications of integrating artificial intelligence (AI) into smartphone technology. The research study goals consist of evaluating the development of AI in mobile phone processors, analyzing the existing state as well as abilities of AI-enabled cpus determining future patterns as well as chances together with reviewing obstacles as well as factors to consider for more growth.

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1. Ana Calin | Senior Software Engineer, Deployments Team, InﬂuxData 27.10.2021 The who, the why and the what of migrating your data. Migrating from OSS to InfluxDB Cloud

8. © 2021 InﬂuxData Inc. All Rights Reserved. Influxdb CLoud # Installs influxdb2 chart from github.com/influxdata/helm-charts/ helm upgrade --install influxdays --namespace influxdays influxdata/influxdb2 --values ~/influxdays-demo/influxdb2_values.yaml # Installs telegraf chart from github.com/influxdata/helm-charts/ helm upgrade --install telegraf --namespace influxdays influxdata/telegraf --values ~/influxdays-demo/telegraf_values.yaml

9. © 2021 InﬂuxData Inc. All Rights Reserved. ~|⇒ kubectl get all -n influxdays NAME READY STATUS RESTARTS AGE pod/influxdays-influxdb2-0 1/1 Running 0 28h pod/telegraf-56798579c7-b4nfj 1/1 Running 0 21h NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE service/influxdays-influxdb2 ClusterIP 10.126.77.243 <none> 80/TCP 28h service/telegraf ClusterIP 10.126.6.166 <none> 8125/UDP 21h NAME READY UP-TO-DATE AVAILABLE AGE deployment.apps/telegraf 1/1 1 1 21h NAME DESIRED CURRENT READY AGE replicaset.apps/telegraf-56798579c7 1 1 1 21h NAME READY AGE statefulset.apps/influxdays-influxdb2 1/1 28h

11. © 2021 InfluxData Inc. All Rights Reserved. © 2021 InfluxData Inc. All Rights Reserved. Prerequisites for migration • an InfluxDB Cloud account with an òrg_id` and bucket name - https://cloud2.influxdata.com/signup • a write token • quick writes headroom • headroom for the cardinality you are adding • a place to hold the LP data x 2 - S3 or GCS or similar

13. © 2021 InfluxData Inc. All Rights Reserved. © 2021 InfluxData Inc. All Rights Reserved. Resources https:/ /cloud2.influxdata.com/signup https:/ /github.com/calinah/influxdays-demo https:/ /docs.influxdata.com/influxdb/v2.0/ref erence/cli/influxd/inspect/export-lp/ https:/ /docs.influxdata.com/influxdb/v2.0/ref erence/sample-data/#noaa-ndbc-data

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