tado° Makes Your Home Environment Smart with InfluxDB

•

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Michal Knizek, Head of Research and Development at tado° GmbH, will share how they use InfluxData to gather data collected from their Smart Thermostat to help turn any home thermostat into a smart device. This device uses a variety of information collected (geo-location, temperature, user settings, current device functional state) to serve information to automatically control the environment temperature as well as letting users know when the device may need maintenance.

tado° Makes Your Home
Environment Smart with
InfluxDB
Michal Knížek, Head of R&D at tado°

tado° R&D
HVAC Technology
HW
Embedded SW
Server SW
Data Analytics
Mobile/web apps

tado° HW Devices

Mobile app
TODO:
ESR

Amazing tado°
Microservices

6LoWPAN Secure WebSocket

“The Constrained Application Protocol (CoAP) is a specialized web
transfer protocol for use with constrained nodes and constrained
networks in the Internet of Things.”

Amazing tado°
Microservices
Boot up
GET /d/SN123456/config
2.05 Content

Amazing tado°
Microservices
Boot up
GET /d/SN123456/config
2.05 Content
PUT /d/config
2.04 Changed
Config change

Amazing tado°
Microservices
Boot up
GET /d/SN123456/config
2.05 Content
PUT /d/config
2.04 Changed
Config change
Timer
GET /d/SN123456/config
2.03 Valid

Ingress
API
Server
WebSocket
HTTP
HTTP

Ingress
API
Server
HTTP
HTTP
…
WebSocket

Ingress…
WebSocket
API
Server
Load
Balancer

…
WebSocket
API
Server
Load
Balancer
Ingress
Load
Balancer
Device
Ingress
Lookup

…
WebSocket
API
Server
Load
Balancer
Ingress
Load
Balancer
Device
Ingress
Lookup

API
Server
TODO:
ESR

API
Server
+JAVA

API
Server

Code example: Java to Influx Query Languages

Challenges
- Fill previous for sparse data
- LAST() query performance
- Data dump
- InfluxData always very helpful!

API
Server
AWS Kinesis
Room
Report
Energy
Savings
Report
S3
DynamoDB

Q & A

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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

Meet the Founders: An Open Discussion About Rewriting Using Rust

Meet the Founders: An Open Discussion About Rewriting Using Rust

Meet the Founders: An Open Discussion About Rewriting Using Rust

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.

Introducing InfluxDB Cloud Dedicated

Introducing InfluxDB Cloud Dedicated

Introducing InfluxDB Cloud Dedicated

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.

Gain Better Observability with OpenTelemetry and InfluxDB

Gain Better Observability with OpenTelemetry and InfluxDB

Gain Better Observability with OpenTelemetry and InfluxDB

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

How a Heat Treating Plant Ensures Tight Process Control and Exceptional Quali...

How a Heat Treating Plant Ensures Tight Process Control and Exceptional Quali...

How a Heat Treating Plant Ensures Tight Process Control and Exceptional Quali...

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

How Delft University's Engineering Students Make Their EV Formula-Style Race ...

How Delft University's Engineering Students Make Their EV Formula-Style Race ...

How Delft University's Engineering Students Make Their EV Formula-Style Race ...

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

Introducing InfluxDB’s New Time Series Database Storage Engine

Introducing InfluxDB’s New Time Series Database Storage Engine

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

Start Automating InfluxDB Deployments at the Edge with balena

Start Automating InfluxDB Deployments at the Edge with balena

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

Understanding InfluxDB’s New Storage Engine

Understanding InfluxDB’s New Storage Engine

Understanding InfluxDB’s New Storage Engine

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

Streamline and Scale Out Data Pipelines with Kubernetes, Telegraf, and InfluxDB

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原版制作美国爱荷华大学毕业证（iowa毕业证书）学位证网上存档可查【Q/微信741003700】原版仿制全套留学文凭材料（毕业证/成绩单（GPA成绩修改）/文凭学历证书/在读证明、毕业完成信、Offer录取通知书)；（真实可查）教育部学历认证、留信网认证、文凭认证、diploma、certificate、Degree、Transcript（实体公司，专业可靠）。 1:1完美还原海外各大学证书上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700。留学生归国服务中心面向美国英国澳洲加拿大留学生提供以下服务: 一、办理毕业证成绩单（学校原版1：1高仿真制作）二、留信认证（留学回国人员学历认证，网上存档可查，查到后付款）三、教育部学历认证（中国教育部留服中心存档可查,查到后付款）办理流程 1、收集客户办理信息； 2、客户付定金下单、公司确认到账转制作点做电子版； 3、电子版做好发给客户确认、电子版确认好转成品部做成品； 4、成品做好拍照或者视频确认再付余款； 5、快递给客户（国内顺丰，国外DHL）。本公司诚聘美国、加拿大、英国、新西兰、澳洲、法国、德国、新加坡各地代理人员，如果你有业余时间有兴趣就请联系我们校园代理，报酬丰厚。真诚期待您的加盟。请联系本公司学历认证顾问(QQ：741003700 微信：741003700)欢迎咨询！最专业的学历顾问，最有经验的顶尖OP为广大留学生的归国之路保卫护航！

原版制作美国爱荷华大学毕业证（iowa毕业证书）学位证网上存档可查

原版制作美国爱荷华大学毕业证（iowa毕业证书）学位证网上存档可查

原版制作美国爱荷华大学毕业证（iowa毕业证书）学位证网上存档可查

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一比一原版(Curtin毕业证书)科廷大学毕业证原件一模一样

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