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All contents © MuleSoft, LLC
Anypoint Runtime Fabric (RTF)
Foundations
Chris Du Preez
Customer Success Strategy & Architecture
October 2020
All contents © MuleSoft Inc.
Agenda
2
1. Introduction: The dilemma
2. Resources
3. Background
4. Considerations
5. RTF Architecture
6. RTF Top Tips
7. When is RTF the right deployment topology for your organisation?
8. Q&A
All contents © MuleSoft, LLC
1. Introductions
The dilemma
All contents © MuleSoft, LLC
The application network platform
Anypoint Platform
On-premises
& private cloud
Hybrid Hosted
by MuleSoft
Cloud service providers
Design
Anypoint Design Center
Scale
Runtime services
Run
Mule
Manage
Anypoint Management Center
Engage
Anypoint Exchange
All contents © MuleSoft, LLC
The application network platform
Anypoint Platform
On-premises
& private cloud
Hybrid Hosted
by MuleSoft
Cloud service providers
Scale
Runtime services
Run
Mule
Design
Anypoint Design Center
Manage
Anypoint Management Center
Engage
Anypoint Exchange
control plane
runtime plane
All contents © MuleSoft, LLC
Background
6
Traditional On-Prem
Multiple years of
investment and refinement
Few modern benefits of
flexibility, self healing
etc. / Self built / High cost
Well understood
architecture
*aaS (Ifra- or Platform)
Containerisation, advanced
availability, scalability etc.
are possible
Still a high level of
investment in non core
capabilities / infra
Some of the Cloud-
Native benefits
Cloud-Native
Infrastructure footprint
reduced, more flexible
commercial model,
scalable, available
Cloud-native practices are
relatively new, perceived
as complex, Lock-in
Full cloud-native
benefits
All contents © MuleSoft, LLC
Background
7
Traditional On-Prem
Multiple years of
investment and refinement
Few modern benefits of
flexibility, self healing
etc. / Self built / High cost
Well understood
architecture
PaaS
Containerisation, advanced
availability, scalability etc.
are possible
Still a high level of
investment in non core
capabilities / infra
Some of the Cloud-
Native benefits
Cloud-Native
Infrastructure footprint
reduced, more flexible
commercial model,
scalable, available
Cloud-native practices are
relatively new, perceived
as complex
Full cloud-native
benefits
On-premise, customer
managed “naked mules”
All contents © MuleSoft, LLC
Background
8
Traditional On-Prem
Multiple years of
investment and refinement
Few modern benefits of
flexibility, self healing
etc. / Self built / High cost
Well understood
architecture
PaaS
Containerisation, advanced
availability, scalability etc.
are possible
Still a high level of
investment in non core
capabilities / infra
Some of the Cloud-
Native benefits
Cloud-Native
Infrastructure footprint
reduced, more flexible
commercial model,
scalable, available
Cloud-native practices are
relatively new, perceived
as complex
Full cloud-native
benefits
Runtime Fabric
On-premise, customer
managed “naked mules”
All contents © MuleSoft, LLC
Background
9
Traditional On-Prem
Multiple years of
investment and refinement
Few modern benefits of
flexibility, self healing
etc. / Self built / High cost
Well understood
architecture
PaaS
Containerisation, advanced
availability, scalability etc.
are possible
Still a high level of
investment in non core
capabilities / infra
Some of the Cloud-
Native benefits
Cloud-Native
Infrastructure footprint
reduced, more flexible
commercial model,
scalable, available
Cloud-native practices are
relatively new, perceived
as complex
Full cloud-native
benefits
Runtime Fabric
On-premise, customer
managed “naked mules”
Cloudhub
All contents © MuleSoft, LLC
1. Introductions
Resources
All contents © MuleSoft, LLC
Short introductory video
● https://www.mulesoft.com/platform/api/multi-cloud-
integration-runtime-fabric
Webinar
● https://www.mulesoft.com/webinars/api/anypoint-runtime-
fabric
Mulesoft documentation site
● https://docs.mulesoft.com/runtime-fabric/1.7/
Training
● https://training.mulesoft.com/course/operations-runtime-fabric
All things Catalyst
● https://catalyst.mulesoft.com/index.action
● Anypoint Platform account login required
Further background
● https://kubernetes.io/docs/tutorials/kubernetes-basics/
● https://docs.docker.com/get-started/overview/
Resources
11
CUSTOMER’S NETWORK
Server Server Server
Mule
App
Mule
App
Mule
App
Runtime Fabric services
Mule
App
Mule
App
Mule
App
Mule
App
Mule
App
Mule
App
Anypoint Runtime Fabric
Control
plane
Docker & Kubernetes
All contents © MuleSoft, LLC
1. Introductions
Background
All contents © MuleSoft, LLC
Why Anypoint Runtime Fabric
Multi / Hybrid Cloud Always Available Low barrier
Background
13
● Azure
● AWS
● VMs
● Bare metal
● High Availability
● Automated Failover
● Increased Isolation
● Rolling upgrades
● Single place to manage
● No Docker knowledge required
● No Kubernetes knowledge
required
All contents © MuleSoft, LLC
● Anypoint Runtime Fabric is a container service
that automates the deployment and
orchestration of Mule applications and API
gateways
● Software appliance installed on customer
infrastructure
○ Azure
○ AWS
○ VMs
○ Bare Metal
What is Anypoint Runtime Fabric?
14
CUSTOMER’S NETWORK
Server Server Server
Mule
App
Mule
App
Mule
App
Runtime Fabric services
Mule
App
Mule
App
Mule
App
Mule
App
Mule
App
Mule
App
Anypoint Runtime Fabric
Control
plane
Docker & Kubernetes
All contents © MuleSoft, LLC
1. Introductions
Considerations
All contents © MuleSoft, LLC
● MuleSoft
○ MuleSoft manages the Runtime Fabric appliance and is
responsible for:
■ Delivered components
■ Runtime Fabric appliance
■ Runtime Fabric agent
■ Mule runtime engine
■ Other dependencies for Mule applications
● Customer
○ Customers are responsible for provisioning, configuring, and
managing the infrastructure required for Runtime Fabric.
○ Infrastructure includes:
○ VM resources (CPU, Memory)
○ Disk performance and capacity
○ Operating systems and kernel patching
○ Network ports
○ Synchronization of system time across all VMs
○ Customers will need their DevOps team
(Infrastructure), Network team (Network ports and
config) and Security team (Compliance and
certificates) to participate in and agree on
configuration
What is Anypoint Runtime Fabric
16
Shared responsibility
All contents © MuleSoft, LLC
Benefits
Capabilities
Consistent deployments across AWS, Azure, VM or Bare Metal
Multiple Runtime Versions in same RTF
Scale horizontally and redeploy w/ zero-downtime
Easily manage via Mulesoft hosted control plane
No resources required to support/maintain orchestration and automation
All contents © MuleSoft, LLC
1. Introductions
RTF Architecture
All contents © MuleSoft, LLC
RTF Architecture
● Anypoint Runtime Fabric is composed of a set
of VMs that form a cluster
● Controller:
○ VM dedicated to operating the RTF
● Worker
○ VM dedicated to running Mule applications
and API Gateways
19
All contents © MuleSoft, LLC
20
Limitations
#Replicas per worker node: Max = 40
#RTFs in Business Group: Max = 50
#Worker Nodes: Max = 16
#Controller Nodes: Max = 5
#Environments per RTF: Max = 50
OS Persistence not currently
supported
Internal Load Balancer - #Reqs (https://
docs.mulesoft.com/runtime-fabric/1.7/runtime-fabric-
limitations)
vCPU
Cores
Max Requests per Second
(Connection Reuse)
Max Requests per Second (No
Connection Reuse)
1.00 2000 175
0.75 1500 100
0.50 1000 50
0.25 100 10
CUSTOMER’S NETWORK
Runtime Fabric services
Anypoint RTF
Control
plane
Docker & Kubernetes
Limitations
All contents © MuleSoft, LLC
RTF Architecture: Development Environments
NOT RECOMMENDED FOR PRODUCTION!
21
All contents © MuleSoft, LLC
RTF Architecture: Production Environments
22
All contents © MuleSoft, LLC
RTF Architecture: Network
23
All contents © MuleSoft, LLC
RTF Architecture: Network
24
All contents © MuleSoft, LLC
1. Introductions
RTF: Top tips to avoid common pitfalls
All contents © MuleSoft, LLC
1. Introductions
Top Tip 1: Resource Allocation
All contents © MuleSoft, LLC
Resource Allocation
● Before deploying an app it is important to understand its resource requirements
● Also important when configuring the internal load balancers inside your RTF
● Each app deployed to RTF has its own runtime instance
○ #Replicas also specified
● Figures quoted here is based on a specific Runtime Fabric cluster configuration on AWS
● You can allocate the following resources when deploying an application:
○ vCPU Cores
■ Reserved vCPU
■ vCPU Limit
○ Memory
https://docs.mulesoft.com/runtime-fabric/1.7/deploy-resource-allocation
● Physical core and Licensed core often differs
● Cannot purchase fractional cores
● License must cover compute power utilised
● To measure utilization use dashboard in Ops Center
CPU and licensed cores
All contents © MuleSoft, LLC
vCPU Allocation
● When the Reserved vCPU and vCPU Limit are equal, the CPU on the worker node is
allocated in a guaranteed model.
● When the value of vCPU Limit is set higher than the value of Reserved vCPU, the
application can burst
● Maximum recommended utilization per CPU core is 20 - 25 simple applications and API
gateways
● CPU limit is upper-bounded by the CPU cores provided on the worker nodes
● RTF runs a small number of services on worker nodes
● Applications compete for unallocated CPU remaining on worker nodes
● Strategies for maximising effective use of unallocated CPU:
○ Deploy nightly batch applications with other apps that process their peak load during
the day
○ Deploy multiple replicas of apps
○ Ensure that you do thorough performance testing!
https://docs.mulesoft.com/runtime-fabric/1.7/deploy-resource-allocation
All contents © MuleSoft, LLC
Memory allocation
● Minimum memory allocation for each replica of Mule application or API Gateway
○ 0.7 GB Mule 4
○ 0.5 GB Mule 3
● Anypoint Monitoring can affect this
● Anypoint Platform allocates native and heap memory for a deployed application.
● Differences in how memory allocation for each memory type is calculated:
○ Runtime Fabric lists the total memory available for an application.
○ CloudHub describes minimum memory requirements in terms of the heap
memory available to an application
https://docs.mulesoft.com/runtime-fabric/1.7/deploy-resource-allocation
All contents © MuleSoft, LLC
Impact of resource allocation
● Resource allocation can impact application startup times and performance of the apps
once started inside RTF
https://docs.mulesoft.com/runtime-fabric/1.7/deploy-resource-allocation
All contents © MuleSoft, LLC
Impact of resource allocation
https://docs.mulesoft.com/runtime-fabric/1.7/deploy-resource-allocation
All contents © MuleSoft, LLC
1. Introductions
Top Tip 2: Hardening
All contents © MuleSoft, LLC
RTF Hardening Checklist
https://docs.mulesoft.com/runtime-fabric/1.7/configure-hardening
All contents © MuleSoft, LLC
1. Introductions
Top Tip 3: Anypoint Security
All contents © MuleSoft, LLC
Anypoint Security
https://docs.mulesoft.com/anypoint-security/
All contents © MuleSoft, LLC
Anypoint Security: Edge Policies
https://docs.mulesoft.com/anypoint-security/
All contents © MuleSoft, LLC
Anypoint Security: Tokenization Service
● Create tokenization services to tokenize sensitive fields from the request payloads.
● Examples:
○ Credit Card Numbers
○ PI information
○ Primary Account Numbers
● Format-preserving tokens can be created
by the Tokenization service
● Tokenization services are deployed to RTFs
https://docs.mulesoft.com/anypoint-security/tokenization
All contents © MuleSoft, LLC
Anypoint Security: Secrets Manager
● Secure vault technology intended to store and control access to:
○ Private keys
○ Passwords
○ Certificates
○ Other secrets
● Designed for use with Anypoint platform
● Supports TLS Context management for:
○ Runtime Fabric ingress
○ API Manager in Cloudhub
● Secret groups can be used
○ Secret groups have unique encryption keys
https://docs.mulesoft.com/anypoint-security/index-secrets-manager
All contents © MuleSoft, LLC
Anypoint Security: Secrets Manager
● Supported Anypoint
Platform services can
request secrets stored in
secrets manager
● Two microservices work
together:
○ Secrets Manager
○ Secrets Provider
https://docs.mulesoft.com/anypoint-security/index-secrets-manager
All contents © MuleSoft, LLC
1. IntroductionsRTF: When is it the deployment topology
for you?
All contents © MuleSoft, LLC
RTF is the correct choice when...
41
Existing cloud
infrastructure
Customer has an AWS or
Azure instance, and can
leverage RTF on their
infrastructure, in some
cases with hybrid cloud.
Ongoing kubernetes
initiatives
RTF is built on kubernetes,
and is attractive to
customers that have
kubernetes initiatives
within their org.
Highly restricted
industries
Customers in industries
such as finance or
government want managed
cloud benefits but can only
deploy on-premises.
Need for automation
and isolation
Current on-premises
deployments are requiring
dedicated teams to monitor
and orchestrate
deployments.
All contents © MuleSoft, LLC
Thank you
All contents © MuleSoft, LLC
1. Introductions
Appendix

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MuleSoft Runtime Fabric (RTF): Foundations : MuleSoft Virtual Muleys Meetups

  • 1. All contents © MuleSoft, LLC Anypoint Runtime Fabric (RTF) Foundations Chris Du Preez Customer Success Strategy & Architecture October 2020
  • 2. All contents © MuleSoft Inc. Agenda 2 1. Introduction: The dilemma 2. Resources 3. Background 4. Considerations 5. RTF Architecture 6. RTF Top Tips 7. When is RTF the right deployment topology for your organisation? 8. Q&A
  • 3. All contents © MuleSoft, LLC 1. Introductions The dilemma
  • 4. All contents © MuleSoft, LLC The application network platform Anypoint Platform On-premises & private cloud Hybrid Hosted by MuleSoft Cloud service providers Design Anypoint Design Center Scale Runtime services Run Mule Manage Anypoint Management Center Engage Anypoint Exchange
  • 5. All contents © MuleSoft, LLC The application network platform Anypoint Platform On-premises & private cloud Hybrid Hosted by MuleSoft Cloud service providers Scale Runtime services Run Mule Design Anypoint Design Center Manage Anypoint Management Center Engage Anypoint Exchange control plane runtime plane
  • 6. All contents © MuleSoft, LLC Background 6 Traditional On-Prem Multiple years of investment and refinement Few modern benefits of flexibility, self healing etc. / Self built / High cost Well understood architecture *aaS (Ifra- or Platform) Containerisation, advanced availability, scalability etc. are possible Still a high level of investment in non core capabilities / infra Some of the Cloud- Native benefits Cloud-Native Infrastructure footprint reduced, more flexible commercial model, scalable, available Cloud-native practices are relatively new, perceived as complex, Lock-in Full cloud-native benefits
  • 7. All contents © MuleSoft, LLC Background 7 Traditional On-Prem Multiple years of investment and refinement Few modern benefits of flexibility, self healing etc. / Self built / High cost Well understood architecture PaaS Containerisation, advanced availability, scalability etc. are possible Still a high level of investment in non core capabilities / infra Some of the Cloud- Native benefits Cloud-Native Infrastructure footprint reduced, more flexible commercial model, scalable, available Cloud-native practices are relatively new, perceived as complex Full cloud-native benefits On-premise, customer managed “naked mules”
  • 8. All contents © MuleSoft, LLC Background 8 Traditional On-Prem Multiple years of investment and refinement Few modern benefits of flexibility, self healing etc. / Self built / High cost Well understood architecture PaaS Containerisation, advanced availability, scalability etc. are possible Still a high level of investment in non core capabilities / infra Some of the Cloud- Native benefits Cloud-Native Infrastructure footprint reduced, more flexible commercial model, scalable, available Cloud-native practices are relatively new, perceived as complex Full cloud-native benefits Runtime Fabric On-premise, customer managed “naked mules”
  • 9. All contents © MuleSoft, LLC Background 9 Traditional On-Prem Multiple years of investment and refinement Few modern benefits of flexibility, self healing etc. / Self built / High cost Well understood architecture PaaS Containerisation, advanced availability, scalability etc. are possible Still a high level of investment in non core capabilities / infra Some of the Cloud- Native benefits Cloud-Native Infrastructure footprint reduced, more flexible commercial model, scalable, available Cloud-native practices are relatively new, perceived as complex Full cloud-native benefits Runtime Fabric On-premise, customer managed “naked mules” Cloudhub
  • 10. All contents © MuleSoft, LLC 1. Introductions Resources
  • 11. All contents © MuleSoft, LLC Short introductory video ● https://www.mulesoft.com/platform/api/multi-cloud- integration-runtime-fabric Webinar ● https://www.mulesoft.com/webinars/api/anypoint-runtime- fabric Mulesoft documentation site ● https://docs.mulesoft.com/runtime-fabric/1.7/ Training ● https://training.mulesoft.com/course/operations-runtime-fabric All things Catalyst ● https://catalyst.mulesoft.com/index.action ● Anypoint Platform account login required Further background ● https://kubernetes.io/docs/tutorials/kubernetes-basics/ ● https://docs.docker.com/get-started/overview/ Resources 11 CUSTOMER’S NETWORK Server Server Server Mule App Mule App Mule App Runtime Fabric services Mule App Mule App Mule App Mule App Mule App Mule App Anypoint Runtime Fabric Control plane Docker & Kubernetes
  • 12. All contents © MuleSoft, LLC 1. Introductions Background
  • 13. All contents © MuleSoft, LLC Why Anypoint Runtime Fabric Multi / Hybrid Cloud Always Available Low barrier Background 13 ● Azure ● AWS ● VMs ● Bare metal ● High Availability ● Automated Failover ● Increased Isolation ● Rolling upgrades ● Single place to manage ● No Docker knowledge required ● No Kubernetes knowledge required
  • 14. All contents © MuleSoft, LLC ● Anypoint Runtime Fabric is a container service that automates the deployment and orchestration of Mule applications and API gateways ● Software appliance installed on customer infrastructure ○ Azure ○ AWS ○ VMs ○ Bare Metal What is Anypoint Runtime Fabric? 14 CUSTOMER’S NETWORK Server Server Server Mule App Mule App Mule App Runtime Fabric services Mule App Mule App Mule App Mule App Mule App Mule App Anypoint Runtime Fabric Control plane Docker & Kubernetes
  • 15. All contents © MuleSoft, LLC 1. Introductions Considerations
  • 16. All contents © MuleSoft, LLC ● MuleSoft ○ MuleSoft manages the Runtime Fabric appliance and is responsible for: ■ Delivered components ■ Runtime Fabric appliance ■ Runtime Fabric agent ■ Mule runtime engine ■ Other dependencies for Mule applications ● Customer ○ Customers are responsible for provisioning, configuring, and managing the infrastructure required for Runtime Fabric. ○ Infrastructure includes: ○ VM resources (CPU, Memory) ○ Disk performance and capacity ○ Operating systems and kernel patching ○ Network ports ○ Synchronization of system time across all VMs ○ Customers will need their DevOps team (Infrastructure), Network team (Network ports and config) and Security team (Compliance and certificates) to participate in and agree on configuration What is Anypoint Runtime Fabric 16 Shared responsibility
  • 17. All contents © MuleSoft, LLC Benefits Capabilities Consistent deployments across AWS, Azure, VM or Bare Metal Multiple Runtime Versions in same RTF Scale horizontally and redeploy w/ zero-downtime Easily manage via Mulesoft hosted control plane No resources required to support/maintain orchestration and automation
  • 18. All contents © MuleSoft, LLC 1. Introductions RTF Architecture
  • 19. All contents © MuleSoft, LLC RTF Architecture ● Anypoint Runtime Fabric is composed of a set of VMs that form a cluster ● Controller: ○ VM dedicated to operating the RTF ● Worker ○ VM dedicated to running Mule applications and API Gateways 19
  • 20. All contents © MuleSoft, LLC 20 Limitations #Replicas per worker node: Max = 40 #RTFs in Business Group: Max = 50 #Worker Nodes: Max = 16 #Controller Nodes: Max = 5 #Environments per RTF: Max = 50 OS Persistence not currently supported Internal Load Balancer - #Reqs (https:// docs.mulesoft.com/runtime-fabric/1.7/runtime-fabric- limitations) vCPU Cores Max Requests per Second (Connection Reuse) Max Requests per Second (No Connection Reuse) 1.00 2000 175 0.75 1500 100 0.50 1000 50 0.25 100 10 CUSTOMER’S NETWORK Runtime Fabric services Anypoint RTF Control plane Docker & Kubernetes Limitations
  • 21. All contents © MuleSoft, LLC RTF Architecture: Development Environments NOT RECOMMENDED FOR PRODUCTION! 21
  • 22. All contents © MuleSoft, LLC RTF Architecture: Production Environments 22
  • 23. All contents © MuleSoft, LLC RTF Architecture: Network 23
  • 24. All contents © MuleSoft, LLC RTF Architecture: Network 24
  • 25. All contents © MuleSoft, LLC 1. Introductions RTF: Top tips to avoid common pitfalls
  • 26. All contents © MuleSoft, LLC 1. Introductions Top Tip 1: Resource Allocation
  • 27. All contents © MuleSoft, LLC Resource Allocation ● Before deploying an app it is important to understand its resource requirements ● Also important when configuring the internal load balancers inside your RTF ● Each app deployed to RTF has its own runtime instance ○ #Replicas also specified ● Figures quoted here is based on a specific Runtime Fabric cluster configuration on AWS ● You can allocate the following resources when deploying an application: ○ vCPU Cores ■ Reserved vCPU ■ vCPU Limit ○ Memory https://docs.mulesoft.com/runtime-fabric/1.7/deploy-resource-allocation ● Physical core and Licensed core often differs ● Cannot purchase fractional cores ● License must cover compute power utilised ● To measure utilization use dashboard in Ops Center CPU and licensed cores
  • 28. All contents © MuleSoft, LLC vCPU Allocation ● When the Reserved vCPU and vCPU Limit are equal, the CPU on the worker node is allocated in a guaranteed model. ● When the value of vCPU Limit is set higher than the value of Reserved vCPU, the application can burst ● Maximum recommended utilization per CPU core is 20 - 25 simple applications and API gateways ● CPU limit is upper-bounded by the CPU cores provided on the worker nodes ● RTF runs a small number of services on worker nodes ● Applications compete for unallocated CPU remaining on worker nodes ● Strategies for maximising effective use of unallocated CPU: ○ Deploy nightly batch applications with other apps that process their peak load during the day ○ Deploy multiple replicas of apps ○ Ensure that you do thorough performance testing! https://docs.mulesoft.com/runtime-fabric/1.7/deploy-resource-allocation
  • 29. All contents © MuleSoft, LLC Memory allocation ● Minimum memory allocation for each replica of Mule application or API Gateway ○ 0.7 GB Mule 4 ○ 0.5 GB Mule 3 ● Anypoint Monitoring can affect this ● Anypoint Platform allocates native and heap memory for a deployed application. ● Differences in how memory allocation for each memory type is calculated: ○ Runtime Fabric lists the total memory available for an application. ○ CloudHub describes minimum memory requirements in terms of the heap memory available to an application https://docs.mulesoft.com/runtime-fabric/1.7/deploy-resource-allocation
  • 30. All contents © MuleSoft, LLC Impact of resource allocation ● Resource allocation can impact application startup times and performance of the apps once started inside RTF https://docs.mulesoft.com/runtime-fabric/1.7/deploy-resource-allocation
  • 31. All contents © MuleSoft, LLC Impact of resource allocation https://docs.mulesoft.com/runtime-fabric/1.7/deploy-resource-allocation
  • 32. All contents © MuleSoft, LLC 1. Introductions Top Tip 2: Hardening
  • 33. All contents © MuleSoft, LLC RTF Hardening Checklist https://docs.mulesoft.com/runtime-fabric/1.7/configure-hardening
  • 34. All contents © MuleSoft, LLC 1. Introductions Top Tip 3: Anypoint Security
  • 35. All contents © MuleSoft, LLC Anypoint Security https://docs.mulesoft.com/anypoint-security/
  • 36. All contents © MuleSoft, LLC Anypoint Security: Edge Policies https://docs.mulesoft.com/anypoint-security/
  • 37. All contents © MuleSoft, LLC Anypoint Security: Tokenization Service ● Create tokenization services to tokenize sensitive fields from the request payloads. ● Examples: ○ Credit Card Numbers ○ PI information ○ Primary Account Numbers ● Format-preserving tokens can be created by the Tokenization service ● Tokenization services are deployed to RTFs https://docs.mulesoft.com/anypoint-security/tokenization
  • 38. All contents © MuleSoft, LLC Anypoint Security: Secrets Manager ● Secure vault technology intended to store and control access to: ○ Private keys ○ Passwords ○ Certificates ○ Other secrets ● Designed for use with Anypoint platform ● Supports TLS Context management for: ○ Runtime Fabric ingress ○ API Manager in Cloudhub ● Secret groups can be used ○ Secret groups have unique encryption keys https://docs.mulesoft.com/anypoint-security/index-secrets-manager
  • 39. All contents © MuleSoft, LLC Anypoint Security: Secrets Manager ● Supported Anypoint Platform services can request secrets stored in secrets manager ● Two microservices work together: ○ Secrets Manager ○ Secrets Provider https://docs.mulesoft.com/anypoint-security/index-secrets-manager
  • 40. All contents © MuleSoft, LLC 1. IntroductionsRTF: When is it the deployment topology for you?
  • 41. All contents © MuleSoft, LLC RTF is the correct choice when... 41 Existing cloud infrastructure Customer has an AWS or Azure instance, and can leverage RTF on their infrastructure, in some cases with hybrid cloud. Ongoing kubernetes initiatives RTF is built on kubernetes, and is attractive to customers that have kubernetes initiatives within their org. Highly restricted industries Customers in industries such as finance or government want managed cloud benefits but can only deploy on-premises. Need for automation and isolation Current on-premises deployments are requiring dedicated teams to monitor and orchestrate deployments.
  • 42. All contents © MuleSoft, LLC Thank you
  • 43. All contents © MuleSoft, LLC 1. Introductions Appendix