Day 2 typos
This commit is contained in:
parent
e2e3b2fdf3
commit
7b1203c7a3
GPG Key ID:
13AFA55AF62F269F
46
.vscode/ltex.dictionary.en-US.txt
vendored
46
.vscode/ltex.dictionary.en-US.txt
vendored
@ -36,3 +36,49 @@ multicluster
|
||||
Statefulset
|
||||
eBPF
|
||||
Parca
|
||||
KubeCon
|
||||
FinOps
|
||||
moondream
|
||||
OLLAMA
|
||||
LLVA
|
||||
LLAVA
|
||||
bokllava
|
||||
NVLink
|
||||
CUDA
|
||||
Space-seperated
|
||||
KAITO
|
||||
Hugginface
|
||||
LLMA
|
||||
Alluxio
|
||||
LLMs
|
||||
onprem
|
||||
Kube
|
||||
Kubeflow
|
||||
Ohly
|
||||
distroless
|
||||
init
|
||||
Distroless
|
||||
Buildkit
|
||||
busybox
|
||||
ECK
|
||||
Kibana
|
||||
Dedup
|
||||
Crossplane
|
||||
autoprovision
|
||||
RBAC
|
||||
Serviceaccount
|
||||
CVEs
|
||||
Podman
|
||||
LinkerD
|
||||
sidecarless
|
||||
Kubeproxy
|
||||
Daemonset
|
||||
zTunnel
|
||||
HBONE
|
||||
Paketo
|
||||
KORFI
|
||||
Traefik
|
||||
traefik
|
||||
Vercel
|
||||
Isovalent
|
||||
CNIs
|
||||
|
||||
@ -6,7 +6,7 @@ tags:
|
||||
- opening
|
||||
---
|
||||
|
||||
The opening keynote started - as is the tradition with keynotes - with an "motivational" opening video.
|
||||
The opening keynote started - as is the tradition with keynotes - with a "motivational" opening video.
|
||||
The keynote itself was presented by the CEO of the CNCF.
|
||||
|
||||
## The numbers
|
||||
@ -26,10 +26,10 @@ The keynote itself was presented by the CEO of the CNCF.
|
||||
## Live demo
|
||||
|
||||
* KIND cluster on desktop
|
||||
* Protptype Stack (develop on client)
|
||||
* Prototype Stack (develop on client)
|
||||
* Kubernetes with the LLM
|
||||
* Host with LLVA (image describe model), moondream and OLLAMA (the model manager/registry()
|
||||
* Host with LLAVA (image describe model), moondream and OLLAMA (the model manager/registry()
|
||||
* Prod Stack (All in kube)
|
||||
* Kubernetes with LLM, LLVA, OLLAMA, moondream
|
||||
* Available Models: llava, mistral bokllava (llava*mistral)
|
||||
* Host takes picture, ai describes what is pictures (in our case the conference audience)
|
||||
* Available Models: LLAVA, mistral bokllava (LLAVA*mistral)
|
||||
* Host takes picture, AI describes what is pictures (in our case the conference audience)
|
||||
|
||||
@ -7,7 +7,7 @@ tags:
|
||||
- panel
|
||||
---
|
||||
|
||||
A podium discussion (somewhat scripted) lead by Pryanka
|
||||
A podium discussion (somewhat scripted) lead by Priyanka
|
||||
|
||||
## Guests
|
||||
|
||||
@ -17,24 +17,24 @@ A podium discussion (somewhat scripted) lead by Pryanka
|
||||
|
||||
## Discussion
|
||||
|
||||
* What do you use as the base of dev for ollama
|
||||
* Jeff: The concepts from docker, git, kubernetes
|
||||
* How is the balance between ai engi and ai ops
|
||||
* Jeff: The classic dev vs ops devide, many ML-Engi don't think about
|
||||
* What do you use as the base of dev for OLLAMA
|
||||
* Jeff: The concepts from docker, git, Kubernetes
|
||||
* How is the balance between AI engineer and AI ops
|
||||
* Jeff: The classic dev vs ops divide, many ML-Engineer don't think about
|
||||
* Paige: Yessir
|
||||
* How does infra keep up with the fast research
|
||||
* Paige: Well, they don't - but they do their best and Cloud native is cool
|
||||
* Jeff: Well we're not google, but kubernetes is the saviour
|
||||
* Jeff: Well we're not google, but Kubernetes is the savior
|
||||
* What are scaling constraints
|
||||
* Jeff: Currently sizing of models is still in it's infancy
|
||||
* Jeff: Currently sizing of models is still in its infancy
|
||||
* Jeff: There will be more specific hardware and someone will have to support it
|
||||
* Paige: Sizing also depends on latency needs (code autocompletion vs performance optimization)
|
||||
* Paige: Optimization of smaller models
|
||||
* What technologies need to be open source licensed
|
||||
* Jeff: The model b/c access and trust
|
||||
* Tim: The models and base execution environemtn -> Vendor agnosticism
|
||||
* Paige: Yes and remixes are really imporant for development
|
||||
* Tim: The models and base execution environment -> Vendor agnosticism
|
||||
* Paige: Yes and remixes are really important for development
|
||||
* Anything else
|
||||
* Jeff: How do we bring our awesome tools (monitoring, logging, security) to the new AI world
|
||||
* Paige: Currently many people just use paid apis to abstract the infra, but we need this stuff selfhostable
|
||||
* Tim: I don'T want to know about the hardware, the whole infra side should be done by the cloudnative teams to let ML-Engi to just be ML-Engine
|
||||
* Paige: Currently many people just use paid APIs to abstract the infra, but we need this stuff self-hostable
|
||||
* Tim: I don't want to know about the hardware, the whole infra side should be done by the cloud native teams to let ML-Engineer to just be ML-Engine
|
||||
|
||||
@ -9,7 +9,7 @@ tags:
|
||||
|
||||
Kevin and Sanjay from NVIDIA
|
||||
|
||||
## Enabeling GPUs in Kubernetes today
|
||||
## Enabling GPUs in Kubernetes today
|
||||
|
||||
* Host level components: Toolkit, drivers
|
||||
* Kubernetes components: Device plugin, feature discovery, node selector
|
||||
@ -18,24 +18,24 @@ Kevin and Sanjay from NVIDIA
|
||||
## GPU sharing
|
||||
|
||||
* Time slicing: Switch around by time
|
||||
* Multi Process Service: Run allways on the GPU but share (space-)
|
||||
* Multi Process Service: Always run on the GPU but share (space-)
|
||||
* Multi Instance GPU: Space-seperated sharing on the hardware
|
||||
* Virtual GPU: Virtualices Time slicing or MIG
|
||||
* Virtual GPU: Virtualizes Time slicing or MIG
|
||||
* CUDA Streams: Run multiple kernels in a single app
|
||||
|
||||
## Dynamic resource allocation
|
||||
|
||||
* A new alpha feature since Kube 1.26 for dynamic ressource requesting
|
||||
* You just request a ressource via the API and have fun
|
||||
* A new alpha feature since Kube 1.26 for dynamic resource requesting
|
||||
* You just request a resource via the API and have fun
|
||||
* The sharing itself is an implementation detail
|
||||
|
||||
## GPU scale out challenges
|
||||
## GPU scale-out challenges
|
||||
|
||||
* NVIDIA Picasso is a foundry for model creation powered by Kubernetes
|
||||
* The workload is the training workload split into batches
|
||||
* Challenge: Schedule multiple training jobs by different users that are prioritized
|
||||
|
||||
### Topology aware placments
|
||||
### Topology aware placements
|
||||
|
||||
* You need thousands of GPUs, a typical Node has 8 GPUs with fast NVLink communication - beyond that switching
|
||||
* Target: optimize related jobs based on GPU node distance and NUMA placement
|
||||
@ -44,11 +44,11 @@ Kevin and Sanjay from NVIDIA
|
||||
|
||||
* Stuff can break, resulting in slowdowns or errors
|
||||
* Challenge: Detect faults and handle them
|
||||
* Observability both in-band and out ouf band that expose node conditions in kubernetes
|
||||
* Observability both in-band and out of band that expose node conditions in Kubernetes
|
||||
* Needed: Automated fault-tolerant scheduling
|
||||
|
||||
### Multi-dimensional optimization
|
||||
### Multidimensional optimization
|
||||
|
||||
* There are different KPIs: starvation, prioprity, occupanccy, fainrness
|
||||
* Challenge: What to choose (the multi-dimensional decision problemn)
|
||||
* There are different KPIs: starvation, priority, occupancy, fairness
|
||||
* Challenge: What to choose (the multidimensional decision problem)
|
||||
* Needed: A scheduler that can balance the dimensions
|
||||
|
||||
@ -20,6 +20,6 @@ Jorge Palma from Microsoft with a quick introduction.
|
||||
* Kubernetes operator that interacts with
|
||||
* Node provisioner
|
||||
* Deployment
|
||||
* Simple CRD that decribes a model, infra and have fun
|
||||
* Creates inferance endpoint
|
||||
* Models are currently 10 (Hugginface, LLMA, etc)
|
||||
* Simple CRD that describes a model, infra and have fun
|
||||
* Creates inference endpoint
|
||||
* Models are currently 10 (Hugginface, LLMA, etc.)
|
||||
|
||||
@ -6,14 +6,14 @@ tags:
|
||||
- panel
|
||||
---
|
||||
|
||||
A panel discussion with moderation by Google and participants from Google, Alluxio, Apmpere and CERN.
|
||||
A panel discussion with moderation by Google and participants from Google, Alluxio, Ampere and CERN.
|
||||
It was pretty scripted with prepared (sponsor specific) slides for each question answered.
|
||||
|
||||
## Takeaways
|
||||
|
||||
* Deploying a ML should become the new deploy a web app
|
||||
* The hardware should be fully utilized -> Better ressource sharing and scheduling
|
||||
* Smaller LLMs on cpu only is preyy cost efficient
|
||||
* Better scheduling by splitting into storage + cpu (prepare) and gpu (run) nodes to create a just-in-time flow
|
||||
* Deploying an ML should become the new deployment a web app
|
||||
* The hardware should be fully utilized -> Better resource sharing and scheduling
|
||||
* Smaller LLMs on CPU only is pretty cost-efficient
|
||||
* Better scheduling by splitting into storage + CPU (prepare) and GPU (run) nodes to create a just-in-time flow
|
||||
* Software acceleration is cool, but we should use more specialized hardware and models to run on CPUs
|
||||
* We should be flexible regarding hardware, multi-cluster workloads and hybrig (onprem, burst to cloud) workloads
|
||||
* We should be flexible regarding hardware, multi-cluster workloads and hybrid (onprem, burst to cloud) workloads
|
||||
|
||||
@ -5,21 +5,21 @@ tags:
|
||||
- keynote
|
||||
---
|
||||
|
||||
Nikhita presented projects that merge CloudNative and AI.
|
||||
PAtrick Ohly Joined for DRA
|
||||
Nikhita presented projects that merge cloud native and AI.
|
||||
Patrick Ohly Joined for DRA
|
||||
|
||||
### The "news"
|
||||
|
||||
* New work group AI
|
||||
* More tools are including ai features
|
||||
* New updated cncf for children feat AI
|
||||
* More tools are including AI features
|
||||
* New updated CNCF for children feat AI
|
||||
* One decade of Kubernetes
|
||||
* DRA is in alpha
|
||||
|
||||
### DRA
|
||||
|
||||
* A new API for resources (node-local and node-attached)
|
||||
* Sharing of ressources between cods and containers
|
||||
* Sharing of resources between cods and containers
|
||||
* Vendor specific stuff are abstracted by a vendor driver controller
|
||||
* The kube scheduler can interact with the vendor parameters for scheduling and autoscaling
|
||||
|
||||
@ -28,18 +28,18 @@ PAtrick Ohly Joined for DRA
|
||||
* Kube is the seed for the AI infra plant
|
||||
* Kubeflow users wanted AI registries
|
||||
* LLM on the edge
|
||||
* Opentelemetry bring semandtics
|
||||
* OpenTelemetry bring semantics
|
||||
* All of these tools form a symbiosis between
|
||||
* Topics of discussions
|
||||
|
||||
### The working group AI
|
||||
|
||||
* It was formed in october 2023
|
||||
* They are working on the whitepaper (cloudnative and ai) wich was opublished on 19.03.2024
|
||||
* The landscape "cloudnative and ai" is WIP and will be merged into the main CNCF landscape
|
||||
* It was formed in October 2023
|
||||
* They are working on the white paper (cloud native and AI) which was published on 19.03.2024
|
||||
* The landscape "cloud native and AI" is WIP and will be merged into the main CNCF landscape
|
||||
* The future focus will be on security and cost efficiency (with a hint of sustainability)
|
||||
|
||||
### LFAI and CNCF
|
||||
|
||||
* The direcor of the AI foundation talks abouzt ai and cloudnative
|
||||
* They are looking forward to more colaboraion
|
||||
* The director of the AI foundation talks about AI and cloud native
|
||||
* They are looking forward to more collaboration
|
||||
|
||||
@ -14,7 +14,7 @@ The entire talk was very short, but it was a nice demo of init containers
|
||||
* Security is hard - distroless sounds like a nice helper
|
||||
* Basic Challenge: Usability-Security Dilemma -> But more usability doesn't mean less secure, but more updating
|
||||
* Distro: Kernel + Software Packages + Package manager (optional) -> In Containers just without the kernel
|
||||
* Distroless: No package manager, no shell, no webcluent (curl/wget) - only minimal sofware bundels
|
||||
* Distroless: No package manager, no shell, no web client (curl/wget) - only minimal software bundles
|
||||
|
||||
## Tools for distroless image creation
|
||||
|
||||
@ -29,13 +29,13 @@ The entire talk was very short, but it was a nice demo of init containers
|
||||
|
||||
## Demo
|
||||
|
||||
* A (rough) distroless postgres with alpine build step and scratch final step
|
||||
* A (rough) distroless Postgres with alpine build step and scratch final step
|
||||
* A basic pg:alpine container used for init with a shared data volume
|
||||
* The init uses the pg admin user to initialize the pg server (you don't need the admin creds after this)
|
||||
* The init uses the pg admin user to initialize the pg server (you don't need the admin credentials after this)
|
||||
|
||||
### Kube
|
||||
|
||||
* K apply failed b/c no internet, but was fixed by connecting to wifi
|
||||
* K apply failed b/c no internet, but was fixed by connecting to Wi-Fi
|
||||
* Without the init container the pod just crashes, with the init container the correct config gets created
|
||||
|
||||
### Docker compose
|
||||
|
||||
@ -13,63 +13,63 @@ A talk by elastic.
|
||||
|
||||
## About elastic
|
||||
|
||||
* Elestic cloud as a managed service
|
||||
* Elastic cloud as a managed service
|
||||
* Deployed across AWS/GCP/Azure in over 50 regions
|
||||
* 600.000+ Containers
|
||||
* 600000+ Containers
|
||||
|
||||
### Elastic and Kube
|
||||
|
||||
* They offer elastic obervability
|
||||
* They offer elastic observability
|
||||
* They offer the ECK operator for simplified deployments
|
||||
|
||||
## The baseline
|
||||
|
||||
* Goal: A large scale (1M+ containers resilient platform on k8s
|
||||
* Goal: A large scale (1M+ containers) resilient platform on k8s
|
||||
* Architecture
|
||||
* Global Control: The control plane (api) for users with controllers
|
||||
* Regional Apps: The "shitload" of kubernetes clusters where the actual customer services live
|
||||
* Global Control: The control plane (API) for users with controllers
|
||||
* Regional Apps: The "shitload" of Kubernetes clusters where the actual customer services live
|
||||
|
||||
## Scalability
|
||||
|
||||
* Challenge: How large can our cluster be, how many clusters do we need
|
||||
* Problem: Only basic guidelines exist for that
|
||||
* Decision: Horizontaly scale the number of clusters (5ßß-1K nodes each)
|
||||
* Decision: Horizontally scale the number of clusters (5ßß-1K nodes each)
|
||||
* Decision: Disposable clusters
|
||||
* Throw away without data loss
|
||||
* Single source of throuth is not cluster etcd but external -> No etcd backups needed
|
||||
* Single source of truth is not cluster etcd but external -> No etcd backups needed
|
||||
* Everything can be recreated any time
|
||||
|
||||
## Controllers
|
||||
|
||||
{{% notice style="note" %}}
|
||||
I won't copy the explanations of operators/controllers in this notes
|
||||
I won't copy the explanations of operators/controllers in these notes
|
||||
{{% /notice %}}
|
||||
|
||||
* Many different controllers, including (but not limited to)
|
||||
* cluster controler: Register cluster to controller
|
||||
* Many controllers, including (but not limited to)
|
||||
* cluster controller: Register cluster to controller
|
||||
* Project controller: Schedule user's project to cluster
|
||||
* Product controllers (Elasticsearch, Kibana, etc.)
|
||||
* Ingress/Cert manager
|
||||
* Sometimes controllers depend on controllers -> potential complexity
|
||||
* Pro:
|
||||
* Resilient (Selfhealing)
|
||||
* Resilient (Self-healing)
|
||||
* Level triggered (desired state vs procedure triggered)
|
||||
* Simple reasoning when comparing desired state vs state machine
|
||||
* Official controller runtime lib
|
||||
* Workque: Automatic Dedup, Retry backoff and so on
|
||||
* Workqueue: Automatic Dedup, Retry back off and so on
|
||||
|
||||
## Global Controllers
|
||||
|
||||
* Basic operation
|
||||
* Uses project config from Elastic cloud as the desired state
|
||||
* The actual state is a k9s ressource in another cluster
|
||||
* Challenge: Where is the source of thruth if the data is not stored in etc
|
||||
* Solution: External datastore (postgres)
|
||||
* Challenge: How do we sync the db sources to kubernetes
|
||||
* The actual state is a k9s resource in another cluster
|
||||
* Challenge: Where is the source of truth if the data is not stored in etcd
|
||||
* Solution: External data store (Postgres)
|
||||
* Challenge: How do we sync the db sources to Kubernetes
|
||||
* Potential solutions: Replace etcd with the external db
|
||||
* Chosen solution:
|
||||
* The controllers don't use CRDs for storage, but they expose a webapi
|
||||
* Reconciliation still now interacts with the external db and go channels (que) instead
|
||||
* The controllers don't use CRDs for storage, but they expose a web-API
|
||||
* Reconciliation still now interacts with the external db and go channels (queue) instead
|
||||
* Then the CRs for the operators get created by the global controller
|
||||
|
||||
### Large scale
|
||||
@ -82,10 +82,10 @@ I won't copy the explanations of operators/controllers in this notes
|
||||
### Reconcile
|
||||
|
||||
* User-driven events are processed asap
|
||||
* reconcole of everything should happen, bus with low prio slowly in the background
|
||||
* Solution: Status: LastReconciledRevision (timestamp) get's compare to revision, if larger -> User change
|
||||
* Prioritization: Just a custom event handler with the normal queue and a low prio
|
||||
* Low Prio Queue: Just a queue that adds items to the normal work-queue with a rate limit
|
||||
* reconcile of everything should happen, bus with low priority slowly in the background
|
||||
* Solution: Status: LastReconciledRevision (timestamp) gets compare to revision, if larger -> User change
|
||||
* Prioritization: Just a custom event handler with the normal queue and a low priority
|
||||
* Queue: Just a queue that adds items to the normal work-queue with a rate limit
|
||||
|
||||
```mermaid
|
||||
flowchart LR
|
||||
|
||||
@ -6,28 +6,28 @@ tags:
|
||||
- security
|
||||
---
|
||||
|
||||
A talk by Google and Microsoft with the premise of bether auth in k8s.
|
||||
A talk by Google and Microsoft with the premise of better auth in k8s.
|
||||
|
||||
## Baselines
|
||||
|
||||
* Most access controllers have read access to all secrets -> They are not really designed for keeping these secrets
|
||||
* Result: CVEs
|
||||
* Example: Just use ingress, nginx, put in some lua code in the config and voila: Service account token
|
||||
* Example: Just use ingress, nginx, put in some Lua code in the config and e voilà: Service account token
|
||||
* Fix: No more fun
|
||||
|
||||
## Basic solutions
|
||||
|
||||
* Seperate Control (the controller) from data (the ingress)
|
||||
* Separate Control (the controller) from data (the ingress)
|
||||
* Namespace limited ingress
|
||||
|
||||
## Current state of cross namespace stuff
|
||||
|
||||
* Why: Reference tls cert for gateway api in the cert team'snamespace
|
||||
* Why: Reference TLS cert for gateway API in the cert team's namespace
|
||||
* Why: Move all ingress configs to one namespace
|
||||
* Classic Solution: Annotations in contour that references a namespace that contains all certs (rewrites secret to certs/secret)
|
||||
* Gateway Solution:
|
||||
* Gateway TLS secret ref includes a namespace
|
||||
* ReferenceGrant pretty mutch allows referencing from X (Gatway) to Y (Secret)
|
||||
* ReferenceGrant pretty much allows referencing from X (Gateway) to Y (Secret)
|
||||
* Limits:
|
||||
* Has to be implemented via controllers
|
||||
* The controllers still have read all - they just check if they are supposed to do this
|
||||
@ -36,9 +36,9 @@ A talk by Google and Microsoft with the premise of bether auth in k8s.
|
||||
|
||||
### Global
|
||||
|
||||
* Grant access to controller to only ressources relevant for them (using references and maybe class segmentation)
|
||||
* Grant access to controller to only resources relevant for them (using references and maybe class segmentation)
|
||||
* Allow for safe cross namespace references
|
||||
* Make it easy for api devs to adopt it
|
||||
* Make it easy for API devs to adopt it
|
||||
|
||||
### Personas
|
||||
|
||||
@ -50,20 +50,20 @@ A talk by Google and Microsoft with the premise of bether auth in k8s.
|
||||
|
||||
* Alex: Define relationships via ReferencePatterns
|
||||
* Kai: Specify controller identity (Serviceaccount), define relationship API
|
||||
* Rohan: Define cross namespace references (aka ressource grants that allow access to their ressources)
|
||||
* Rohan: Define cross namespace references (aka resource grants that allow access to their resources)
|
||||
|
||||
## Result of the paper
|
||||
|
||||
### Architecture
|
||||
|
||||
* ReferencePattern: Where do i find the references -> example: GatewayClass in the gateway API
|
||||
* ReferenceConsumer: Who (IOdentity) has access under which conditions?
|
||||
* ReferenceConsumer: Who (Identity) has access under which conditions?
|
||||
* ReferenceGrant: Allow specific references
|
||||
|
||||
### POC
|
||||
|
||||
* Minimum access: You only get access if the grant is there AND the reference actually exists
|
||||
* Their basic implementation works with the kube api
|
||||
* Their basic implementation works with the kube API
|
||||
|
||||
### Open questions
|
||||
|
||||
@ -74,9 +74,9 @@ A talk by Google and Microsoft with the premise of bether auth in k8s.
|
||||
|
||||
## Alternative
|
||||
|
||||
* Idea: Just extend RBAC Roles with a selector (match labels, etc)
|
||||
* Idea: Just extend RBAC Roles with a selector (match labels, etc.)
|
||||
* Problems:
|
||||
* Requires changes to kubernetes core auth
|
||||
* Requires changes to Kubernetes core auth
|
||||
* Everything bus list and watch is a pain
|
||||
* How do you handle AND vs OR selection
|
||||
* Field selectors: They exist
|
||||
@ -84,5 +84,5 @@ A talk by Google and Microsoft with the premise of bether auth in k8s.
|
||||
|
||||
## Meanwhile
|
||||
|
||||
* Prefer tools that support isolatiobn between controller and dataplane
|
||||
* Prefer tools that support isolation between controller and data-plane
|
||||
* Disable all non-needed features -> Especially scripting
|
||||
|
||||
@ -7,31 +7,31 @@ tags:
|
||||
---
|
||||
|
||||
A talk by UX and software people at Red Hat (Podman team).
|
||||
The talk mainly followed the academic study process (aka this is the survey I did for my bachelors/masters thesis).
|
||||
The talk mainly followed the academic study process (aka this is the survey I did for my bachelor's/master's thesis).
|
||||
|
||||
## Research
|
||||
|
||||
* User research Study including 11 devs and platform engineers over three months
|
||||
* Focus was on an new podman desktop feature
|
||||
* Experence range 2-3 years experience average (low no experience, high oldschool kube)
|
||||
* Focus was on a new Podman desktop feature
|
||||
* Experience range 2-3 years experience average (low no experience, high old school kube)
|
||||
* 16 questions regarding environment, workflow, debugging and pain points
|
||||
* Analysis: Affinity mapping
|
||||
|
||||
## Findings
|
||||
|
||||
* Where do I start when things are broken? -> There may be solutions, but devs don't know about them
|
||||
* Network debugging is hard b/c many layers and problems occuring in between cni and infra are really hard -> Network topology issues are rare but hard
|
||||
* YAML identation -> Tool support is needed for visualisation
|
||||
* YAML validation -> Just use validation in dev and gitops
|
||||
* YAML Cleanup -> Normalize YAML (order, anchors, etc) for easy diff
|
||||
* Inadequate security analysis (too verbose, non-issues are warnings) -> Realtime insights (and during dev)
|
||||
* Network debugging is hard b/c many layers and problems occurring in between CNI and infra are really hard -> Network topology issues are rare but hard
|
||||
* YAML indentation -> Tool support is needed for visualization
|
||||
* YAML validation -> Just use validation in dev and GitOps
|
||||
* YAML Cleanup -> Normalize YAML (order, anchors, etc.) for easy diff
|
||||
* Inadequate security analysis (too verbose, non-issues are warnings) -> Real-time insights (and during dev)
|
||||
* Crash Loop -> Identify stuck containers, simple debug containers
|
||||
* CLI vs GUI -> Enable eperience level oriented gui, Enhance intime troubleshooting
|
||||
* CLI vs GUI -> Enable experience level oriented GUI, Enhance in-time troubleshooting
|
||||
|
||||
## General issues
|
||||
|
||||
* No direct fs access
|
||||
* Multiple kubeconfigs
|
||||
* SaaS is sometimes only provided on kube, which sounds like complexity
|
||||
* Where do i begin my troubleshooting
|
||||
* Where do I begin my troubleshooting
|
||||
* Interoperability/Fragility with updates
|
||||
|
||||
@ -10,7 +10,7 @@ Global field CTO at Solo.io with a hint of servicemesh background.
|
||||
|
||||
## History
|
||||
|
||||
* LinkerD 1.X was the first moder servicemesh and basicly a opt-in serviceproxy
|
||||
* LinkerD 1.X was the first modern service mesh and basically an opt-in service proxy
|
||||
* Challenges: JVM (size), latencies, ...
|
||||
|
||||
### Why not node-proxy?
|
||||
@ -23,8 +23,8 @@ Global field CTO at Solo.io with a hint of servicemesh background.
|
||||
### Why sidecar?
|
||||
|
||||
* Transparent (ish)
|
||||
* PArt of app lifecycle (up/down)
|
||||
* Single tennant
|
||||
* Part of app lifecycle (up/down)
|
||||
* Single tenant
|
||||
* No noisy neighbor
|
||||
|
||||
### Sidecar drawbacks
|
||||
@ -46,7 +46,7 @@ Global field CTO at Solo.io with a hint of servicemesh background.
|
||||
|
||||
* Full transparency
|
||||
* Optimized networking
|
||||
* Lower ressource allocation
|
||||
* Lower resource allocation
|
||||
* No race conditions
|
||||
* No manual pod injection
|
||||
* No credentials in the app
|
||||
@ -68,12 +68,12 @@ Global field CTO at Solo.io with a hint of servicemesh background.
|
||||
* Kubeproxy replacement
|
||||
* Ingress (via Gateway API)
|
||||
* Mutual Authentication
|
||||
* Specialiced CiliumNetworkPolicy
|
||||
* Configure Envoy throgh Cilium
|
||||
* Specialized CiliumNetworkPolicy
|
||||
* Configure Envoy through Cilium
|
||||
|
||||
### Control Plane
|
||||
|
||||
* Cilium-Agent on each node that reacts to scheduled workloads by programming the local dataplane
|
||||
* Cilium-Agent on each node that reacts to scheduled workloads by programming the local data-plane
|
||||
* API via Gateway API and CiliumNetworkPolicy
|
||||
|
||||
```mermaid
|
||||
@ -98,29 +98,29 @@ flowchart TD
|
||||
### Data plane
|
||||
|
||||
* Configured by control plane
|
||||
* Does all of the eBPF things in L4
|
||||
* Does all of the envoy things in L7
|
||||
* In-Kernel Wireguard for optional transparent encryption
|
||||
* Does all the eBPF things in L4
|
||||
* Does all the envoy things in L7
|
||||
* In-Kernel WireGuard for optional transparent encryption
|
||||
|
||||
### mTLS
|
||||
|
||||
* Network Policies get applied at the eBPF layer (check if id a can talk to id 2)
|
||||
* When mTLS is enabled there is a auth check in advance -> It it fails, proceed with agents
|
||||
* Agents talk to each other for mTLS Auth and save the result to a cache -> Now ebpf can say yes
|
||||
* Problems: The caches can lead to id confusion
|
||||
* Network Policies get applied at the eBPF layer (check if ID a can talk to ID 2)
|
||||
* When mTLS is enabled there is an auth check in advance -> If it fails, proceed with agents
|
||||
* Talk to each other for mTLS Auth and save the result to a cache -> Now eBPF can say yes
|
||||
* Problems: The caches can lead to ID confusion
|
||||
|
||||
## Istio
|
||||
|
||||
### Basiscs
|
||||
### Basics
|
||||
|
||||
* L4/7 Service mesh without it's own CNI
|
||||
* L4/7 Service mesh without its own CNI
|
||||
* Based on envoy
|
||||
* mTLS
|
||||
* Classicly via sidecar, nowadays
|
||||
* Classically via sidecar, nowadays
|
||||
|
||||
### Ambient mode
|
||||
|
||||
* Seperate L4 and L7 -> Can run on cilium
|
||||
* Separate L4 and L7 -> Can run on cilium
|
||||
* mTLS
|
||||
* Gateway API
|
||||
|
||||
@ -143,14 +143,14 @@ flowchart TD
|
||||
```
|
||||
|
||||
* Central xDS Control Plane
|
||||
* Per-Node Dataplane that reads updates from Control Plane
|
||||
* Per-Node Data-plane that reads updates from Control Plane
|
||||
|
||||
### Data Plane
|
||||
|
||||
* L4 runs via zTunnel Daemonset that handels mTLS
|
||||
* The zTunnel traffic get's handed over to the CNI
|
||||
* L7 Proxy lives somewhere™ and traffic get's routed through it as an "extra hop" aka waypoint
|
||||
* L4 runs via zTunnel Daemonset that handles mTLS
|
||||
* The zTunnel traffic gets handed over to the CNI
|
||||
* L7 Proxy lives somewhere™ and traffic gets routed through it as an "extra hop" aka waypoint
|
||||
|
||||
### mTLS
|
||||
|
||||
* The zTunnel creates a HBONE (http overlay network) tunnel with mTLS
|
||||
* The zTunnel creates a HBONE (HTTP overlay network) tunnel with mTLS
|
||||
|
||||
@ -8,7 +8,7 @@ Who have I talked to today, are there any follow-ups or learnings?
|
||||
## Operator Framework
|
||||
|
||||
* We talked about the operator lifecycle manager
|
||||
* They shared the roadmap and the new release 1.0 will bring support for Operator Bundle loading from any oci source (no more public-registry enforcement)
|
||||
* They shared the roadmap and the new release 1.0 will bring support for Operator Bundle loading from any OCI source (no more public-registry enforcement)
|
||||
|
||||
## Flux
|
||||
|
||||
@ -17,8 +17,8 @@ Who have I talked to today, are there any follow-ups or learnings?
|
||||
## Cloud foundry/Paketo
|
||||
|
||||
* We mostly had some smalltalk
|
||||
* There will be a cloudfoundry day in Karlsruhe in October, they'd be happy to have us ther
|
||||
* The whole KORFI (Cloudfoundry on Kubernetes) Project is still going strong, but no release canidate yet (or in the near future)
|
||||
* There will be a cloud foundry day in Karlsruhe in October, they'd be happy to have us there
|
||||
* The whole KORFI (Cloud foundry on Kubernetes) Project is still going strong, but no release candidate yet (or in the near future)
|
||||
|
||||
## Traefik
|
||||
|
||||
@ -31,7 +31,7 @@ They will follow up
|
||||
## Postman
|
||||
|
||||
* I asked them about their new cloud-only stuff: They will keep their direction
|
||||
* The are also planning to work on info materials on why postman SaaS is not a big security risk
|
||||
* They are also planning to work on info materials on why postman SaaS is not a big security risk
|
||||
|
||||
## Mattermost
|
||||
|
||||
@ -39,9 +39,9 @@ They will follow up
|
||||
I should follow up
|
||||
{{% /notice %}}
|
||||
|
||||
* I talked about our problems with the mattermost operator and was asked to get back to them with the errors
|
||||
* They're currently migrating the mattermost cloud offering to arm - therefor arm support will be coming in the next months
|
||||
* The mattermost guy had exactly the same problems with notifications and read/unread using element
|
||||
* I talked about our problems with the Mattermost operator and was asked to get back to them with the errors
|
||||
* They're currently migrating the Mattermost cloud offering to arm - therefor arm support will be coming in the next months
|
||||
* The Mattermost guy had exactly the same problems with notifications and read/unread using element
|
||||
|
||||
## Vercel
|
||||
|
||||
@ -63,11 +63,11 @@ I should follow up
|
||||
They will follow up with a quick demo
|
||||
{{% /notice %}}
|
||||
|
||||
* A kubernetes security/runtime security solution with pretty nice looking urgency filters
|
||||
* A Kubernetes security/runtime security solution with pretty nice looking urgency filters
|
||||
* Includes eBPF to see what code actually runs
|
||||
* I'll witness a demo in early/mid april
|
||||
* I'll witness a demo in early/mid April
|
||||
|
||||
### Isovalent
|
||||
|
||||
* Dinner (very tasty)
|
||||
* Cilium still sounds like the way to go in regards to CNIs
|
||||
* Cilium still sounds like the way to go in regard to CNIs
|
||||
|
||||
@ -5,7 +5,7 @@ weight: 2
|
||||
---
|
||||
|
||||
Day two is also the official day one of KubeCon (Day one was just CloudNativeCon).
|
||||
This is where all of the people joined (over 12000)
|
||||
This is where all the people joined (over 12000)
|
||||
|
||||
The opening keynotes were a mix of talks and panel discussions.
|
||||
The main topic was - who could have guessed - AI and ML.
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user