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Google Cloud Computing compares GCE, GAE and GKE
Google Cloud Computing compares GCE, GKE and GAE. GCE provides raw compute, storage and networking resources and requires more management overhead. GAE focuses on application logic and requires less management. GKE offers managed Kubernetes infrastructure and services. Each option has different strengths for workloads like microservices, containerized services, or large-scale applications requiring quick scaling. Monitoring and management features like Stackdriver are also compared.
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Google Cloud Computing compares GCE, GAE and GKE
- 1. Google Cloud Computingcompares GCE, GKE and GAE Simon Su @ GCPUG.TW
- 2. I’m Simon Su... varsimon = {/** I am at GCPUG.TW **/}; simon.GDE = 'https://developers.google.com/experts/people/peihsin-su'; simon.nodejs = ‘http://opennodes.arecord.us'; simon.googleshare = 'http://gappsnews.blogspot.tw' simon.nodejsblog = ‘http://nodejs-in-example.blogspot.tw'; simon.blog = ‘http://peihsinsu.blogspot.com'; simon.slideshare = ‘http://slideshare.net/peihsinsu/'; simon.email = ‘simonsu.mail@gmail.com’; simon.say(‘Let’s go Cloud!');
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- 4. Google Cloud Platform BigQuery BigData Pub/Sub Dataflow Dataproc Datalab Compute Compute EngineApp Engine Container Engine Storage Cloud Storage Cloud SQL Cloud Datastore Bigtable Machine Learning Speech API Machine Learning Translate APIVision APINatural Language API
- 5. GCE Compute Engine - GCEVM, Disk, Network - Load Balancer - Instance Group
- 6. GAE App Engine - StandardRuntime - Flexible Runtime - Standard Env - Custom Env
- 7. GKE Container Engine - Docker& rkt - Pod, deployment - Service vs. NLB - Ingress vs. HLB - Scaling
- 8. Getting Start… You wantto deploy...
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- 11. What we careabout... ● Loading high ● Run out of resource ● Management ● Monitoring & alert ● Cost ● ...
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- 17. Container Code and libraries Container Codeand libraries Container Code and libraries Container Code and libraries
- 18. GCE / GKE/ GAE PaaS Preset run-times Java, Go, PHP, Python... Focus is application logic Pay for what you use Less management overhead IaaS Raw compute, storage and network More granular control Pay for what you allocate More management overhead Towards managed infrastructure Towards managed services Compute Engine App EngineContainer Engine
- 19. - restrictions and conditions -dockerized service - micro services - fast scale - no limitation GCE / GKE / GAE need to do before use Towards managed infrastructure Towards managed services Compute Engine App EngineContainer Engine - operation & monitor - architecture planning
- 20. - more integrated pricing -daily free 28 instance/hour quota - master node managed by google - at last 1 worker node - extend base on template vm size GCE / GKE / GAE compares in Cost Towards managed infrastructure Towards managed services Compute Engine App EngineContainer Engine - custom node size / scalable pricing - load balancer pricing
- 21. - web services withlarge scaling - need quick scale - using GAE services - micro services - containerized services - plan to cross cloud GCE / GKE / GAE good for... Towards managed infrastructure Towards managed services Compute Engine App EngineContainer Engine - small scale for small service deploy - large scale for high performance service
- 22. There are morefeatures...
- 23. GCE ~ more ~ Functional ●Integrated cloud permissions ● Routing and firewalls ● Snapshot ● Images ● Custom machine type Pricing ● Sustain pricing ● Sub-hour billing
- 24. GAE ~ more ~ Project AppEngine App Servers Application instances Application instances Application instances Task queues Scheduled tasks Search Memcache Logs
- 25. ● Federation clustering ●Auto scaling ● GCE resource integrated ○ HLB as K8S Ingress ○ NLB as K8S Service ● Secret ● GKE UI ● Host auto-scaling ● Version upgrade & management ● Container registry (gcr.io) ● Image builder GKE ~ more ~
- 26. StackDriver All you usedin GCP can be Monitored….
- 27. Monitoring Platform, system, and applicationmetrics Uptime/health checks Dashboards and alerts Logging Platform, system, and application logs Log search/view/filter Log-based metrics Trace Latency reporting and sampling Per-URL latency and statistics Error Reporting Error notifications Error dashboard Debugger Debug applications
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