SlideShare ist ein Scribd-Unternehmen logo

Real time metrics with rickshaw and nodejs

•Als PPTX, PDF herunterladen•
•
Hakka Labs
Hakka Labs

Rickshaw is a JavaScript toolkit for creating interactive time series graphs. Rickshaw allows you to build interactive time series d3.js charts. ntf is a suite of components to make it easy to test and monitor the state of your network services and applications. ntf is a network testing framework written in Node.js. lil-brother helps Shutterstock understand how their customers are interacting with their site. Written in Node.js Lil-Brother tracks clicks on web pages, without blocking any interaction.

Technologie
1 von 29
Real time metrics with rickshaw and nodejs
Real time metrics with rickshaw and nodejs
Real time metrics with rickshaw and nodejs
Real time metrics with rickshaw and nodejs
Real time metrics with rickshaw and nodejs
Real time metrics with rickshaw and nodejs
Real time metrics with rickshaw and nodejs
Real time metrics with rickshaw and nodejs
Real time metrics with rickshaw and nodejs
Real time metrics with rickshaw and nodejs
Real time metrics with rickshaw and nodejs
Real time metrics with rickshaw and nodejs
Real time metrics with rickshaw and nodejs
Real time metrics with rickshaw and nodejs
Real time metrics with rickshaw and nodejs
Real time metrics with rickshaw and nodejs
Real time metrics with rickshaw and nodejs
Real time metrics with rickshaw and nodejs
Real time metrics with rickshaw and nodejs
Real time metrics with rickshaw and nodejs
Real time metrics with rickshaw and nodejs
Real time metrics with rickshaw and nodejs
Real time metrics with rickshaw and nodejs
Real time metrics with rickshaw and nodejs
Real time metrics with rickshaw and nodejs
Real time metrics with rickshaw and nodejs
Real time metrics with rickshaw and nodejs
Real time metrics with rickshaw and nodejs
Real time metrics with rickshaw and nodejs

Empfohlen

Measure your app internals with InfluxDB and Symfony2
Measure your app internals with InfluxDB and Symfony2Measure your app internals with InfluxDB and Symfony2
Measure your app internals with InfluxDB and Symfony2Corley S.r.l.
 
Always Valid Inference (Ramesh Johari, Stanford)
Always Valid Inference (Ramesh Johari, Stanford)Always Valid Inference (Ramesh Johari, Stanford)
Always Valid Inference (Ramesh Johari, Stanford)Hakka Labs
 
DataEngConf SF16 - High cardinality time series search
DataEngConf SF16 - High cardinality time series searchDataEngConf SF16 - High cardinality time series search
DataEngConf SF16 - High cardinality time series searchHakka Labs
 
DataEngConf SF16 - Data Asserts: Defensive Data Science
DataEngConf SF16 - Data Asserts: Defensive Data ScienceDataEngConf SF16 - Data Asserts: Defensive Data Science
DataEngConf SF16 - Data Asserts: Defensive Data ScienceHakka Labs
 
DatEngConf SF16 - Apache Kudu: Fast Analytics on Fast Data
DatEngConf SF16 - Apache Kudu: Fast Analytics on Fast DataDatEngConf SF16 - Apache Kudu: Fast Analytics on Fast Data
DatEngConf SF16 - Apache Kudu: Fast Analytics on Fast DataHakka Labs
 
DataEngConf SF16 - Recommendations at Instacart
DataEngConf SF16 - Recommendations at InstacartDataEngConf SF16 - Recommendations at Instacart
DataEngConf SF16 - Recommendations at InstacartHakka Labs
 
DataEngConf SF16 - Running simulations at scale
DataEngConf SF16 - Running simulations at scaleDataEngConf SF16 - Running simulations at scale
DataEngConf SF16 - Running simulations at scaleHakka Labs
 
DataEngConf SF16 - Deriving Meaning from Wearable Sensor Data
DataEngConf SF16 - Deriving Meaning from Wearable Sensor DataDataEngConf SF16 - Deriving Meaning from Wearable Sensor Data
DataEngConf SF16 - Deriving Meaning from Wearable Sensor DataHakka Labs
 

Empfohlen

Measure your app internals with InfluxDB and Symfony2
Measure your app internals with InfluxDB and Symfony2Measure your app internals with InfluxDB and Symfony2
Measure your app internals with InfluxDB and Symfony2Corley S.r.l.
 
Always Valid Inference (Ramesh Johari, Stanford)
Always Valid Inference (Ramesh Johari, Stanford)Always Valid Inference (Ramesh Johari, Stanford)
Always Valid Inference (Ramesh Johari, Stanford)Hakka Labs
 
DataEngConf SF16 - High cardinality time series search
DataEngConf SF16 - High cardinality time series searchDataEngConf SF16 - High cardinality time series search
DataEngConf SF16 - High cardinality time series searchHakka Labs
 
DataEngConf SF16 - Data Asserts: Defensive Data Science
DataEngConf SF16 - Data Asserts: Defensive Data ScienceDataEngConf SF16 - Data Asserts: Defensive Data Science
DataEngConf SF16 - Data Asserts: Defensive Data ScienceHakka Labs
 
DatEngConf SF16 - Apache Kudu: Fast Analytics on Fast Data
DatEngConf SF16 - Apache Kudu: Fast Analytics on Fast DataDatEngConf SF16 - Apache Kudu: Fast Analytics on Fast Data
DatEngConf SF16 - Apache Kudu: Fast Analytics on Fast DataHakka Labs
 
DataEngConf SF16 - Recommendations at Instacart
DataEngConf SF16 - Recommendations at InstacartDataEngConf SF16 - Recommendations at Instacart
DataEngConf SF16 - Recommendations at InstacartHakka Labs
 
DataEngConf SF16 - Running simulations at scale
DataEngConf SF16 - Running simulations at scaleDataEngConf SF16 - Running simulations at scale
DataEngConf SF16 - Running simulations at scaleHakka Labs
 
DataEngConf SF16 - Deriving Meaning from Wearable Sensor Data
DataEngConf SF16 - Deriving Meaning from Wearable Sensor DataDataEngConf SF16 - Deriving Meaning from Wearable Sensor Data
DataEngConf SF16 - Deriving Meaning from Wearable Sensor DataHakka Labs
 
DataEngConf SF16 - Collecting and Moving Data at Scale
DataEngConf SF16 - Collecting and Moving Data at Scale DataEngConf SF16 - Collecting and Moving Data at Scale
DataEngConf SF16 - Collecting and Moving Data at Scale Hakka Labs
 
DataEngConf SF16 - BYOMQ: Why We [re]Built IronMQ
DataEngConf SF16 - BYOMQ: Why We [re]Built IronMQDataEngConf SF16 - BYOMQ: Why We [re]Built IronMQ
DataEngConf SF16 - BYOMQ: Why We [re]Built IronMQHakka Labs
 
DataEngConf SF16 - Unifying Real Time and Historical Analytics with the Lambd...
DataEngConf SF16 - Unifying Real Time and Historical Analytics with the Lambd...DataEngConf SF16 - Unifying Real Time and Historical Analytics with the Lambd...
DataEngConf SF16 - Unifying Real Time and Historical Analytics with the Lambd...Hakka Labs
 
DataEngConf SF16 - Three lessons learned from building a production machine l...
DataEngConf SF16 - Three lessons learned from building a production machine l...DataEngConf SF16 - Three lessons learned from building a production machine l...
DataEngConf SF16 - Three lessons learned from building a production machine l...Hakka Labs
 
DataEngConf SF16 - Scalable and Reliable Logging at Pinterest
DataEngConf SF16 - Scalable and Reliable Logging at PinterestDataEngConf SF16 - Scalable and Reliable Logging at Pinterest
DataEngConf SF16 - Scalable and Reliable Logging at PinterestHakka Labs
 
DataEngConf SF16 - Bridging the gap between data science and data engineering
DataEngConf SF16 - Bridging the gap between data science and data engineeringDataEngConf SF16 - Bridging the gap between data science and data engineering
DataEngConf SF16 - Bridging the gap between data science and data engineeringHakka Labs
 
DataEngConf SF16 - Multi-temporal Data Structures
DataEngConf SF16 - Multi-temporal Data StructuresDataEngConf SF16 - Multi-temporal Data Structures
DataEngConf SF16 - Multi-temporal Data StructuresHakka Labs
 
DataEngConf SF16 - Entity Resolution in Data Pipelines Using Spark
DataEngConf SF16 - Entity Resolution in Data Pipelines Using SparkDataEngConf SF16 - Entity Resolution in Data Pipelines Using Spark
DataEngConf SF16 - Entity Resolution in Data Pipelines Using SparkHakka Labs
 
DataEngConf SF16 - Beginning with Ourselves
DataEngConf SF16 - Beginning with OurselvesDataEngConf SF16 - Beginning with Ourselves
DataEngConf SF16 - Beginning with OurselvesHakka Labs
 
DataEngConf SF16 - Routing Billions of Analytics Events with High Deliverability
DataEngConf SF16 - Routing Billions of Analytics Events with High DeliverabilityDataEngConf SF16 - Routing Billions of Analytics Events with High Deliverability
DataEngConf SF16 - Routing Billions of Analytics Events with High DeliverabilityHakka Labs
 
DataEngConf SF16 - Tales from the other side - What a hiring manager wish you...
DataEngConf SF16 - Tales from the other side - What a hiring manager wish you...DataEngConf SF16 - Tales from the other side - What a hiring manager wish you...
DataEngConf SF16 - Tales from the other side - What a hiring manager wish you...Hakka Labs
 
DataEngConf SF16 - Methods for Content Relevance at LinkedIn
DataEngConf SF16 - Methods for Content Relevance at LinkedInDataEngConf SF16 - Methods for Content Relevance at LinkedIn
DataEngConf SF16 - Methods for Content Relevance at LinkedInHakka Labs
 
DataEngConf SF16 - Spark SQL Workshop
DataEngConf SF16 - Spark SQL WorkshopDataEngConf SF16 - Spark SQL Workshop
DataEngConf SF16 - Spark SQL WorkshopHakka Labs
 
DataEngConf: Building a Music Recommender System from Scratch with Spotify Da...
DataEngConf: Building a Music Recommender System from Scratch with Spotify Da...DataEngConf: Building a Music Recommender System from Scratch with Spotify Da...
DataEngConf: Building a Music Recommender System from Scratch with Spotify Da...Hakka Labs
 
DataEngConf: Data Science at the New York Times by Chris Wiggins
DataEngConf: Data Science at the New York Times by Chris WigginsDataEngConf: Data Science at the New York Times by Chris Wiggins
DataEngConf: Data Science at the New York Times by Chris WigginsHakka Labs
 
DataEngConf: Building the Next New York Times Recommendation Engine
DataEngConf: Building the Next New York Times Recommendation EngineDataEngConf: Building the Next New York Times Recommendation Engine
DataEngConf: Building the Next New York Times Recommendation EngineHakka Labs
 
DataEngConf: Measuring Impact with Data in a Distributed World at Conde Nast
DataEngConf: Measuring Impact with Data in a Distributed World at Conde NastDataEngConf: Measuring Impact with Data in a Distributed World at Conde Nast
DataEngConf: Measuring Impact with Data in a Distributed World at Conde NastHakka Labs
 
DataEngConf: Feature Extraction: Modern Questions and Challenges at Google
DataEngConf: Feature Extraction: Modern Questions and Challenges at GoogleDataEngConf: Feature Extraction: Modern Questions and Challenges at Google
DataEngConf: Feature Extraction: Modern Questions and Challenges at GoogleHakka Labs
 
DataEngConf: Talkographics: Using What Viewers Say Online to Measure TV and B...
DataEngConf: Talkographics: Using What Viewers Say Online to Measure TV and B...DataEngConf: Talkographics: Using What Viewers Say Online to Measure TV and B...
DataEngConf: Talkographics: Using What Viewers Say Online to Measure TV and B...Hakka Labs
 
DataEngConf: The Science of Virality at BuzzFeed
DataEngConf: The Science of Virality at BuzzFeedDataEngConf: The Science of Virality at BuzzFeed
DataEngConf: The Science of Virality at BuzzFeedHakka Labs
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonAnna Loughnan Colquhoun
 
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slidevu2urc
 

Weitere ähnliche Inhalte

Mehr von Hakka Labs

DataEngConf SF16 - Collecting and Moving Data at Scale
DataEngConf SF16 - Collecting and Moving Data at Scale DataEngConf SF16 - Collecting and Moving Data at Scale
DataEngConf SF16 - Collecting and Moving Data at Scale Hakka Labs
 
DataEngConf SF16 - BYOMQ: Why We [re]Built IronMQ
DataEngConf SF16 - BYOMQ: Why We [re]Built IronMQDataEngConf SF16 - BYOMQ: Why We [re]Built IronMQ
DataEngConf SF16 - BYOMQ: Why We [re]Built IronMQHakka Labs
 
DataEngConf SF16 - Unifying Real Time and Historical Analytics with the Lambd...
DataEngConf SF16 - Unifying Real Time and Historical Analytics with the Lambd...DataEngConf SF16 - Unifying Real Time and Historical Analytics with the Lambd...
DataEngConf SF16 - Unifying Real Time and Historical Analytics with the Lambd...Hakka Labs
 
DataEngConf SF16 - Three lessons learned from building a production machine l...
DataEngConf SF16 - Three lessons learned from building a production machine l...DataEngConf SF16 - Three lessons learned from building a production machine l...
DataEngConf SF16 - Three lessons learned from building a production machine l...Hakka Labs
 
DataEngConf SF16 - Scalable and Reliable Logging at Pinterest
DataEngConf SF16 - Scalable and Reliable Logging at PinterestDataEngConf SF16 - Scalable and Reliable Logging at Pinterest
DataEngConf SF16 - Scalable and Reliable Logging at PinterestHakka Labs
 
DataEngConf SF16 - Bridging the gap between data science and data engineering
DataEngConf SF16 - Bridging the gap between data science and data engineeringDataEngConf SF16 - Bridging the gap between data science and data engineering
DataEngConf SF16 - Bridging the gap between data science and data engineeringHakka Labs
 
DataEngConf SF16 - Multi-temporal Data Structures
DataEngConf SF16 - Multi-temporal Data StructuresDataEngConf SF16 - Multi-temporal Data Structures
DataEngConf SF16 - Multi-temporal Data StructuresHakka Labs
 
DataEngConf SF16 - Entity Resolution in Data Pipelines Using Spark
DataEngConf SF16 - Entity Resolution in Data Pipelines Using SparkDataEngConf SF16 - Entity Resolution in Data Pipelines Using Spark
DataEngConf SF16 - Entity Resolution in Data Pipelines Using SparkHakka Labs
 
DataEngConf SF16 - Beginning with Ourselves
DataEngConf SF16 - Beginning with OurselvesDataEngConf SF16 - Beginning with Ourselves
DataEngConf SF16 - Beginning with OurselvesHakka Labs
 
DataEngConf SF16 - Routing Billions of Analytics Events with High Deliverability
DataEngConf SF16 - Routing Billions of Analytics Events with High DeliverabilityDataEngConf SF16 - Routing Billions of Analytics Events with High Deliverability
DataEngConf SF16 - Routing Billions of Analytics Events with High DeliverabilityHakka Labs
 
DataEngConf SF16 - Tales from the other side - What a hiring manager wish you...
DataEngConf SF16 - Tales from the other side - What a hiring manager wish you...DataEngConf SF16 - Tales from the other side - What a hiring manager wish you...
DataEngConf SF16 - Tales from the other side - What a hiring manager wish you...Hakka Labs
 
DataEngConf SF16 - Methods for Content Relevance at LinkedIn
DataEngConf SF16 - Methods for Content Relevance at LinkedInDataEngConf SF16 - Methods for Content Relevance at LinkedIn
DataEngConf SF16 - Methods for Content Relevance at LinkedInHakka Labs
 
DataEngConf SF16 - Spark SQL Workshop
DataEngConf SF16 - Spark SQL WorkshopDataEngConf SF16 - Spark SQL Workshop
DataEngConf SF16 - Spark SQL WorkshopHakka Labs
 
DataEngConf: Building a Music Recommender System from Scratch with Spotify Da...
DataEngConf: Building a Music Recommender System from Scratch with Spotify Da...DataEngConf: Building a Music Recommender System from Scratch with Spotify Da...
DataEngConf: Building a Music Recommender System from Scratch with Spotify Da...Hakka Labs
 
DataEngConf: Data Science at the New York Times by Chris Wiggins
DataEngConf: Data Science at the New York Times by Chris WigginsDataEngConf: Data Science at the New York Times by Chris Wiggins
DataEngConf: Data Science at the New York Times by Chris WigginsHakka Labs
 
DataEngConf: Building the Next New York Times Recommendation Engine
DataEngConf: Building the Next New York Times Recommendation EngineDataEngConf: Building the Next New York Times Recommendation Engine
DataEngConf: Building the Next New York Times Recommendation EngineHakka Labs
 
DataEngConf: Measuring Impact with Data in a Distributed World at Conde Nast
DataEngConf: Measuring Impact with Data in a Distributed World at Conde NastDataEngConf: Measuring Impact with Data in a Distributed World at Conde Nast
DataEngConf: Measuring Impact with Data in a Distributed World at Conde NastHakka Labs
 
DataEngConf: Feature Extraction: Modern Questions and Challenges at Google
DataEngConf: Feature Extraction: Modern Questions and Challenges at GoogleDataEngConf: Feature Extraction: Modern Questions and Challenges at Google
DataEngConf: Feature Extraction: Modern Questions and Challenges at GoogleHakka Labs
 
DataEngConf: Talkographics: Using What Viewers Say Online to Measure TV and B...
DataEngConf: Talkographics: Using What Viewers Say Online to Measure TV and B...DataEngConf: Talkographics: Using What Viewers Say Online to Measure TV and B...
DataEngConf: Talkographics: Using What Viewers Say Online to Measure TV and B...Hakka Labs
 
DataEngConf: The Science of Virality at BuzzFeed
DataEngConf: The Science of Virality at BuzzFeedDataEngConf: The Science of Virality at BuzzFeed
DataEngConf: The Science of Virality at BuzzFeedHakka Labs
 

Mehr von Hakka Labs (20)

DataEngConf SF16 - Collecting and Moving Data at Scale
DataEngConf SF16 - Collecting and Moving Data at Scale DataEngConf SF16 - Collecting and Moving Data at Scale
DataEngConf SF16 - Collecting and Moving Data at Scale
 
DataEngConf SF16 - BYOMQ: Why We [re]Built IronMQ
DataEngConf SF16 - BYOMQ: Why We [re]Built IronMQDataEngConf SF16 - BYOMQ: Why We [re]Built IronMQ
DataEngConf SF16 - BYOMQ: Why We [re]Built IronMQ
 
DataEngConf SF16 - Unifying Real Time and Historical Analytics with the Lambd...
DataEngConf SF16 - Unifying Real Time and Historical Analytics with the Lambd...DataEngConf SF16 - Unifying Real Time and Historical Analytics with the Lambd...
DataEngConf SF16 - Unifying Real Time and Historical Analytics with the Lambd...
 
DataEngConf SF16 - Three lessons learned from building a production machine l...
DataEngConf SF16 - Three lessons learned from building a production machine l...DataEngConf SF16 - Three lessons learned from building a production machine l...
DataEngConf SF16 - Three lessons learned from building a production machine l...
 
DataEngConf SF16 - Scalable and Reliable Logging at Pinterest
DataEngConf SF16 - Scalable and Reliable Logging at PinterestDataEngConf SF16 - Scalable and Reliable Logging at Pinterest
DataEngConf SF16 - Scalable and Reliable Logging at Pinterest
 
DataEngConf SF16 - Bridging the gap between data science and data engineering
DataEngConf SF16 - Bridging the gap between data science and data engineeringDataEngConf SF16 - Bridging the gap between data science and data engineering
DataEngConf SF16 - Bridging the gap between data science and data engineering
 
DataEngConf SF16 - Multi-temporal Data Structures
DataEngConf SF16 - Multi-temporal Data StructuresDataEngConf SF16 - Multi-temporal Data Structures
DataEngConf SF16 - Multi-temporal Data Structures
 
DataEngConf SF16 - Entity Resolution in Data Pipelines Using Spark
DataEngConf SF16 - Entity Resolution in Data Pipelines Using SparkDataEngConf SF16 - Entity Resolution in Data Pipelines Using Spark
DataEngConf SF16 - Entity Resolution in Data Pipelines Using Spark
 
DataEngConf SF16 - Beginning with Ourselves
DataEngConf SF16 - Beginning with OurselvesDataEngConf SF16 - Beginning with Ourselves
DataEngConf SF16 - Beginning with Ourselves
 
DataEngConf SF16 - Routing Billions of Analytics Events with High Deliverability
DataEngConf SF16 - Routing Billions of Analytics Events with High DeliverabilityDataEngConf SF16 - Routing Billions of Analytics Events with High Deliverability
DataEngConf SF16 - Routing Billions of Analytics Events with High Deliverability
 
DataEngConf SF16 - Tales from the other side - What a hiring manager wish you...
DataEngConf SF16 - Tales from the other side - What a hiring manager wish you...DataEngConf SF16 - Tales from the other side - What a hiring manager wish you...
DataEngConf SF16 - Tales from the other side - What a hiring manager wish you...
 
DataEngConf SF16 - Methods for Content Relevance at LinkedIn
DataEngConf SF16 - Methods for Content Relevance at LinkedInDataEngConf SF16 - Methods for Content Relevance at LinkedIn
DataEngConf SF16 - Methods for Content Relevance at LinkedIn
 
DataEngConf SF16 - Spark SQL Workshop
DataEngConf SF16 - Spark SQL WorkshopDataEngConf SF16 - Spark SQL Workshop
DataEngConf SF16 - Spark SQL Workshop
 
DataEngConf: Building a Music Recommender System from Scratch with Spotify Da...
DataEngConf: Building a Music Recommender System from Scratch with Spotify Da...DataEngConf: Building a Music Recommender System from Scratch with Spotify Da...
DataEngConf: Building a Music Recommender System from Scratch with Spotify Da...
 
DataEngConf: Data Science at the New York Times by Chris Wiggins
DataEngConf: Data Science at the New York Times by Chris WigginsDataEngConf: Data Science at the New York Times by Chris Wiggins
DataEngConf: Data Science at the New York Times by Chris Wiggins
 
DataEngConf: Building the Next New York Times Recommendation Engine
DataEngConf: Building the Next New York Times Recommendation EngineDataEngConf: Building the Next New York Times Recommendation Engine
DataEngConf: Building the Next New York Times Recommendation Engine
 
DataEngConf: Measuring Impact with Data in a Distributed World at Conde Nast
DataEngConf: Measuring Impact with Data in a Distributed World at Conde NastDataEngConf: Measuring Impact with Data in a Distributed World at Conde Nast
DataEngConf: Measuring Impact with Data in a Distributed World at Conde Nast
 
DataEngConf: Feature Extraction: Modern Questions and Challenges at Google
DataEngConf: Feature Extraction: Modern Questions and Challenges at GoogleDataEngConf: Feature Extraction: Modern Questions and Challenges at Google
DataEngConf: Feature Extraction: Modern Questions and Challenges at Google
 
DataEngConf: Talkographics: Using What Viewers Say Online to Measure TV and B...
DataEngConf: Talkographics: Using What Viewers Say Online to Measure TV and B...DataEngConf: Talkographics: Using What Viewers Say Online to Measure TV and B...
DataEngConf: Talkographics: Using What Viewers Say Online to Measure TV and B...
 
DataEngConf: The Science of Virality at BuzzFeed
DataEngConf: The Science of Virality at BuzzFeedDataEngConf: The Science of Virality at BuzzFeed
DataEngConf: The Science of Virality at BuzzFeed
 

Kürzlich hochgeladen

Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonAnna Loughnan Colquhoun
 
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slidevu2urc
 
Slack Application Development 101 Slides
Slack Application Development 101 SlidesSlack Application Development 101 Slides
Slack Application Development 101 Slidespraypatel2
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationRadu Cotescu
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountPuma Security, LLC
 
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Igalia
 
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEarley Information Science
 
🐬 The future of MySQL is Postgres 🐘
🐬 The future of MySQL is Postgres 🐘🐬 The future of MySQL is Postgres 🐘
🐬 The future of MySQL is Postgres 🐘RTylerCroy
 
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdfhans926745
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)Gabriella Davis
 
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Miguel Araújo
 
Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityBoost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityPrincipled Technologies
 
Artificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsArtificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsJoaquim Jorge
 
A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024Results
 
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdfUnderstanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdfUK Journal
 
Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024The Digital Insurer
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerThousandEyes
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...Martijn de Jong
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Scriptwesley chun
 
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfThe Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfEnterprise Knowledge
 

Kürzlich hochgeladen (20)

Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt Robison
 
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slide
 
Slack Application Development 101 Slides
Slack Application Development 101 SlidesSlack Application Development 101 Slides
Slack Application Development 101 Slides
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organization
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path Mount
 
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
 
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
 
🐬 The future of MySQL is Postgres 🐘
🐬 The future of MySQL is Postgres 🐘🐬 The future of MySQL is Postgres 🐘
🐬 The future of MySQL is Postgres 🐘
 
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)
 
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
 
Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityBoost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivity
 
Artificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsArtificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and Myths
 
A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024
 
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdfUnderstanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
 
Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Script
 
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfThe Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf