Event page: https://meetups.mulesoft.com/events/details/mulesoft-calgary-presents-exploring-the-rtf-deployment-model/

1. All contents © MuleSoft, LLC
Sandeep Deshmukh (Technical Architect) -New York
Amit Jha (Senior Solutions Architect) - New York
Mandy Wong (API & Integration Specialist) - Calgary
Jimmy Attia (Senior Strategic Advisor) - Edmonton
Exploring the Runtime Fabric
Deployment Model
Online Meetup

2. All contents © MuleSoft, LLC
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Speakers
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Sandeep Deshmukh
Customer Success
Technical Architect
5 years IT experience. MuleSoft
Architect certified. Provides API
governance for organization and
develops API’s for projects. Advocate of
accelerating digital transformation
through API’s.
8+ years IT experience. MuleSoft
Architect/Developer certified with
expertise in CloudHub and
Runtime Fabric deployment
topologies. Strong advocate of
process and technical efficiencies.
Mandy Wong
API & Integration
Specialist
Amit Jha
Senior Solutions
Architect
5+ years of experience in various
MuleSoft deployment topology
models like CloudHub, Runtime
Fabric and Standalone. Sound
knowledge of Service Oriented
Architecture, object-oriented
concepts, analysis and design of
applications architecture.
Jimmy Attia
Senior Strategic
Advisor
As a Senior Strategic Advisor with
Mulesoft's Customer Success
Strategy and Architecture team, I
provide leadership and strategic
advisory services to Mulesoft
customers across a variety of
topics and activities like
integration architecture and
organization enablement

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Agenda
1. Meetup Logistics
2. Customer Perspective
3. Different Deployment models
4. Introduction to Runtime Fabric
5. Runtime Fabric Appliance vs Runtime Fabric on Self-Managed Kubernetes
6. Trivia
7. Demo / Q & A
a. Migrating Applications from CloudHub to Runtime Fabric
b. Preventing Common Pitfalls when configuring Runtime Fabric
8. Trivia Winners
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Meeting Logistics
● The session is recorded and a copy will be sent to the registrants following the event
● Attendees are placed on mute upon entry
● Feel free to post your questions in the chat and we will answer them at the end
● We will have 3 trivia questions between segments and the winners will be announced at the end
● Instructions will be provided before the trivia questions for valid participation
● Prize: each winner will get a voucher for a free MuleSoft course
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Customer perspective

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RTF implementation Challenges
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● Benefits of going to RTF versus fully cloud - why do all this work rather than just allowing
MuleSoft to manage our API’s?
● Differences between going with RTF on VM/Bare Metal versus a Self-managed Kubernetes
EKS/AKS cluster -> Things to consider?
● When migrating API projects from on-prem to RTF, it is known that several or most
connectors will behave differently. What are key things to keep in mind and prevent projects
from “breaking” when moving to RTF?
● How will CI/CD tools change moving from on-prem to RTF, such as GitHub and Jenkins
pipelines?

8. All contents © MuleSoft, LLC
RTF implementation Challenges
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● How can we best set-up our infrastructure on self-managed Kubernetes to support RTF?
● What are the best practices for achieving API security in RTF?
● When decommissioning API’s, how do we go about it in RTF? In general, how do we manage
the API lifecycle in RTF?

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Deployment Models

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Anypoint Platform
11
On-premises
& private cloud
Hybrid Hosted
by MuleSoft
Cloud service providers
OPERATE
DESIGN
DEPLOY
BUILD
ENGAGE

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Anypoint Platform
12
On-premises
& private cloud
Hybrid Hosted
by MuleSoft
Cloud service providers
OPERATE
DESIGN
DEPLOY
BUILD
ENGAGE
Management/Control Plane

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Anypoint Platform
13
On-premises
& private cloud
Hybrid Hosted
by MuleSoft
Cloud service providers
OPERATE
DESIGN
DEPLOY
BUILD
ENGAGE
Runtime Plane

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Deployment Models
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Anypoint Platform Management
Mule Runtime
Key
Fully Managed Cloud
(CloudHub)
Hybrid Deployment
Deployed:
Cloud
Deployed:
On-prem /
Private
IaaS
Managed by
Managed by
MuleSoft MuleSoft
Customer
MuleSoft
On-Premise Runtimes Fully On-Premise (PCE)
Customer Customer
Runtime Fabric (RTF)
Appliance/ RTF services:
MuleSoft
Infrastructure: Customer
MuleSoft

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Deciding on a Deployment Topology
• Built in HA through RTF services
• Tokenization, Edge Security, Secrets
Manager
• Runtime Manager Monitoring:
– Built-in Anypoint Monitoring
Dashboard
– Or Classic Application
Monitoring
• Configurable HA and clustering
• Runtime Manager Monitoring:
– Classic Application Monitoring
– Server/Groups/Cluster Monitoring
dashboard
• Anypoint Monitoring can be configured
using an AM agent or external
monitoring configured (refer to
documentation)
• Built in HA through multiple worker
clouds
• AnypointMQ, Secrets Manager
• Runtime Manager Monitoring:
– Built-in Anypoint Monitoring
Dashboard
– Or Classic Application Monitoring
Deployments Feature Comparison

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• Deploy consistently across any
cloud (Azure & AWS) or data center
• Run multiple runtime versions in the
same Runtime Fabric
• Isolate apps, scale horizontally,
redeploy w/ zero-downtime
• Connect to the control plane hosted
by MuleSoft
• Deployment flexibility across any cloud
(Azure & AWS) or data center
• Integrations can run in same data
center as customer applications
• Satisfies potential data sovereignty
issues
• Connect to the control plane hosted by
MuleSoft
• Runtime managed by MuleSoft in
CloudHub - can be separate regions to
control plane
• No configuration needed - just worker
size and number
• Built-in re-start, HA across availability
zones
• Additional services available e.g. Anypoint
MQ, Secrets Manager, ObjectStore
Deciding on a Deployment Topology
Deployments Benefits Comparison

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Introduction to Runtime Fabric

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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.
Anypoint Platform: Runtime Fabric
Where does it fit?

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Anypoint Runtime Fabric
Deploy and manage runtimes across any cloud
Centrally manage all applications
Manage applications in your private cloud
(AWS, Azure) and CloudHub within Anypoint
Platform
Run Mule apps on Kubernetes
Get containerization benefits such as isolation,
horizontal scaling, and auto redeploy by
default
Move deployments in a few clicks
Pivot your deployments between CloudHub,
your private cloud, or a data center with no
impact

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Runtime Fabric (RTF) is delivered to
customers as a software appliance to
run on their premises.
Customers bring their own hardware
and networking, and install RTF on top
of it.
Customers maintain the infrastructure,
and MuleSoft maintains the Kubernetes
stack, RTF services and Mule
deployments.
Note: Appliance refers to the MuleSoft provided
kubernetes stack which includes Docker, Kubernetes,
Flannel, Ops Center.
Runtime Fabric Appliance - RTF on VM/Bare Metal
VM
Mule
App
VM
Mule
App
Mule
App
Runtime Fabric components
Runtime Fabric appliance
Mule
App
network
Runtime Fabric on VM/Bare Metal
Mule
App
Mule
App
VM
Customer Managed
MuleSoft Managed

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Shared Responsibility Model
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Server Server Server
Server Server
Runtime Fabric services
Server
Docker & Kubernetes (workers)
Docker & Kubernetes (masters)
Runtime Fabric services
Controller VMs
Worker VMs
Anypoint Platform: Runtime Fabric
● Ingress Controller
(Edge)
● Upgrades
● Docker Reg
● Ops Center
● Runtime
● Init
● Log fwd
Mule Mule Mule Mule Mule Mule Mule Mule Mule Mule Mule Mule
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What’s inside a Production ‘Fabric’

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Runtime Fabric is delivered to customers as a
package of components/services that run on
top of an existing EKS or AKS environment.
Customers bring their own Kubernetes,
ingress controller, and external log forwarding
and install RTF within it.
Customers maintain the health of Kubernetes,
and MuleSoft maintains the RTF services and
Mule deployments.
Note: RTF Services examples: RTF agent, Anypoint
Monitoring agent etc.
*New* Runtime Fabric on EKS / AKS
Node
Mule
App
Node
Mule
App
Mule
App
Runtime Fabric services
EKS or AKS
Mule
App
network
Runtime Fabric on EKS / AKS
Mule
App
Mule
App
Node
Customer Managed
(K8s specialist)
Managed within Anypoint Platform

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Extend control plane benefits to
runtimes on your AKS or EKS
● Customer gets the latest
management and monitoring
features of Anypoint Platform
Decouple Mule runtime services
from your own infrastructure
● Give your ops teams the
power to use their
infrastructure how they want
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CUSTOMER’S NETWORK
Mule
App
Mule
App
Mule
App
Runtime Fabric services
Mule
App
Mule
App
Mule
App
Mule
App
Mule
App
Mule
App
Runtime Plane
CONTROL
PLANE
Kubernetes-as-a-Service
Deploy and manage runtimes on your own AKS or EKS
RTF on AKS/EKS

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RTF on VM/Bare Metal (Production
Configuration)
Runtime Fabric – VM/Bare Metal vs AKS/EKS
RTF on AKS/EKS (Default Configuration)
Option 1 Option 2

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● EKS / AKS are highly available and
managed by cloud provider
thereby freeing up developer time
to focus on integration/API
development.
● Managed worker nodes simplify
node scaling and upgrades.
● More customizable to your
organization’s environment.
● Choose your own ingress
controller and log forwarding
agents.
Lower Cost
Benefits of RTF on AKS/EKS
More Flexible
● AKS / EKS replaces the
controller nodes.
● Lower infrastructure costs
with Azure/AWS.
Less Overhead

26. All contents © MuleSoft, LLC
Key Feature Changes Summary
RTF on EKS/AKS RTF on VM/ Bare Metal
Support for deploying Mules and API Gateways Supported. Supported.
Kubernetes and Docker Not included; customers bring their own
via provisioning EKS or AKS clusters.
Included.
Support for installing on any Linux distribution Supported. RHEL and CentOS only.
Support for node auto-scaling Supported using Azure or AWS settings. Not supported.
Support for external log forwarding Customers bring their own external log
forwarder.
Included.
Support for internal load balancer Customers bring their own internal load
balancer (called “Ingress Controller”)
Included.
Support for Anypoint Security Edge Not supported. Supported.
Ops Center Not included (Anypoint Monitoring still
supported). Customers can enable similar
monitoring and alerting from AWS or
Azure console.
Included.

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What’s behind an application deployment
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Application deployment process
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Key points
Two major steps
● Upload the application package to the Exchange
● Deploy from Exchange
Key component to check in deployment issues
● The communication between agent and the control plane
● The registry-creds job
● The init container

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Performance Tools
RTF Demo

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RTF implementation Challenges

31. All contents © MuleSoft, LLC
RTF implementation Challenges
38
● Benefits of going to RTF versus fully cloud - why do all this work rather than just allowing
MuleSoft to manage our API’s?
● Differences between going with RTF on VM/Bare Metal versus a Self-managed Kubernetes
EKS/AKS cluster -> Things to consider?
● When migrating API projects from on-prem to RTF, it is known that several or most
connectors will behave differently. What are key things to keep in mind and prevent projects
from “breaking” when moving to RTF?
● How will CI/CD tools change moving from on-prem to RTF, such as GitHub and Jenkins
pipelines?

32. All contents © MuleSoft, LLC
RTF implementation Challenges
39
● How can we best set-up our infrastructure on self-managed Kubernetes to support RTF?
● What are the best practices for achieving API security in RTF?
● When decommissioning API’s, how do we go about it in RTF? In general, how do we manage
the API lifecycle in RTF?

33. All contents © MuleSoft, LLC
1) Blog for on-prem to RTF migration: http://mule.is/bUzsHC
2)Runtime Fabric: https://docs.mulesoft.com/runtime-fabric/latest/
2) MuleSoft Documentation: https://docs.mulesoft.com/general/
3) Catalyst KnowledgeHub: http://catalyst.mulesoft.com/
Appendix
Some useful Links: