Author: David (Page 13 of 24)

PKS, Harbor and the importance of container registries

February 27, 2019 / David / 0 Comments

What are container registries and why do we need them?

A lot of the time, particularly when individuals and organisations are evaluating, testing and experimenting with containers they will use public container registries such as Docker Hub. These public registries provide an easy-to-use, simple way to access images. As developers, application owners, system admins etc gain familiarity and experience additional operational considerations need to be explored, such as:

Organisation – How can we organise container images in a meaningful way? Such as by environment state (Prod/Dev/Test) and application type?
RBAC – How can we implement role-based access control to a container registry?
Vulnerability Scanning – How can we scan container images for known vulnerabilities?
Efficiency – How can we centrally manage all our container images and deploy an application from them?
Security – Some images need to kept under lock and key, rather than using an external service like Docker Hub.

Introducing VMware Harbor Registry

VMware Harbor Registry has been designed to address these considerations as enterprise-class container registry solution with integration into PKS. In this post, We’ll have a quick primer on getting up and running with Harbor in PKS and explore some of its features. To begin, we need to download PKS Harbor from the Pivotal site and import it into ops manager.

After which the tile will be added (When doing this for the first time it will have an orange bar at the bottom. Press the tile to configure).

The following need to be defined with applicable parameters to suit your environment.

Availability Zone and Networks – This is where the Harbor VM will reside, and the respective configuration will be dependent on your setup.
General – Hostname and IP address settings
Certificate – Generate a self-signed certificate, or BYOC (bring your own certificate)
Credentials – Define the local admin password
Authentication – Choose between
- Internal
- LDAP
- UAA in PKS
- UAA in PAS
Container Registry store – Choose where to store container images pushed to Harbor
- Local file system
- NFS Server
- S3 Bucket
- Google Cloud Storage
Clair Proxy Settings
Notary settings
Resource Config

VMware Harbor Registry – Organisation

Harbor employs the concept of “projects”. Projects are a way of collecting images for a specific application or service. When images are pushed to Harbor, they reside within a project:

Projects can either be private or public and can be configured during, or after, project creation:

A project is comprised of a number of components:

VMware Harbor Registry – RBAC

In Harbor, we have three role types we can assign to projects:

rbac

Image source: https://github.com/goharbor/harbor/blob/master/docs/user_guide.md#managing-projects

Guest – Read-only access, can pull images
Developer – Read/write access, can pull and push images
Admin – Read/Write access, as well as project-level activities, such as modifying parameters and permissions.

As a practical example, AD groups can be created to facilitate these roles:

And these AD groups can be mapped to respective permissions within the project

Therefore, facilitating RBAC within our Harbor environment. Pretty handy.

VMware Harbor Registry – Vulnerability Scanning

The ability to identify, evaluate and remediate vulnerabilities is a standard operation is modern software development and deployment. Thankfully Harbor addresses this with integration with Clair – an open source project that addresses the identification, categorisation and analysis of vulnerabilities within containers. As a demonstration we need to first push an image to Harbor:

After initiating a scan, Harbor can inform us of what vulnerabilities exist within this container image

We can then explore more details about these vulnerabilities, including when they were fixed:

Conclusion

Harbor provides us with an enterprise level, container registry solution. This blog post has only scratched the surface, and with constant development being invested into the project, expect more features and improvements.

Efficiency gains from small(er) containers

February 11, 2019 / David / 0 Comments

Preamble

A lot of organisations are looking towards containerising their applications and embracing the world of microservices. There are a number of ways to reach this goal, through a variety of tools and methodologies, this blog post goes through one way of approaching this task.

In a previous blog post I went through the process of taking a web application and putting it into a container, and whilst it got the job done, there wasn’t a lot of attention given to the image used for the container. So let’s address that.

Container images come in all shapes and sizes and choosing the right base for your application can be a difficult decision.

VM vs Ubuntu Container vs NGINX Container

In the aforementioned blog post, I took a simple web application and placed it into a Ubuntu-based container. It worked fine, but is there any way we can further optimise it?

I’ve got a generic 18.04 Ubuntu Server VM I spun up, installed Apache2 and added in my web application. According to the hypervisor (ESXi in this case), the VM consumed 5.84GB of storage

Next, I’ll do the same in a Ubuntu container, using the Ubuntu image as my base:

But what about different base images?

NGINX is is an open source reverse proxy server for HTTP, HTTPS, SMTP, POP3, and IMAP, as well as a load balancer, HTTP cache, and a web server. As such. it’s more specialised than the standard Ubuntu image. So let’s create another image based on NGINX.

Apache also has a image, so lets throw that in for good measure.

Comparing all three images yield different results with regards to image size:

Unsurprisingly, the Ubuntu base image comes in as the largest, followed by the Apache image, and NGINX being the smallest.

Is this such a big deal, though? If we consider:

The potential number of pods
The time taken for new nodes to download the image
The lifecycle of a pod

Then shaving off even 100MB or so from an image can have a significant impact on operations.

Thought process

From this exercise, we can determine one approach to choosing the right base image could be a result of the following:

vRealize Log Insight + PKS Integration

February 2, 2019 / David / 3 Comments

Introduction

In this blog post, we take a look into the integration between PKS and vRealize Log Insight and how this integration benefits the enterprise. As a bit of a recap:

PKS – PKS is a purpose-built enterprise level container solution leveraging the capabilities of Kubernetes, BOSH, VMware NSX-T, Harbour and more to deliver a highly available, highly flexible container runtime that operates on a number of cloud platforms, both private and public, including vSphere, AWS, Azure and GCP.

VMware also released VMware Cloud PKS, a fully managed service that combines the technical capabilities of AWS, PKS and Kuberntes which can be consumed in a similar fashion to other cloud services.

vRealize Log Insight – vRealize Log Insight is a log management system that’s designed to operate within heterogeneous environments, however, it’s much more than a simple aggregator of logging information. vRealize Log Insight has analytical and trend-identification capabilities which allow operators to gain invaluable insight into the state, health, and events which are transpiring in the environment. vRealize Log Insight works across physical, virtual and cloud environments.

Containers and Coexistence with VM’s

VM’s have existed for a long time now. Consequently, there are very mature, battle-hardened tools and software which can be used to monitor a plethora of operating systems, software, components and more. Containers, on the other hand, are relatively new in the enterprise. Although there is an overlap, there are significant differences in the way we monitor and collect logs from VM’s and containers. How can this be addressed?

There are a number of ways to monitor a container based environment. Prometheus and Wavefront come to mind, but for environments that already leverage vRealize Log Insight, we can integrate PKS with it to facilitate a single plane of glass view of logging information from VM’s, their underlying infrastructure as well as containers and their underlying infrastructure.

What can we expect PKS to send to Log Insight

At a high level, the Integration between PKS and vRLI will facilitate the propagation of the following logs:

BOSH jobs
Core Kubernetes processes & nodes
Core BOSH processes
Kubernetes event logs
Individual Pod stdout and stderr

I’ve highlighted the last one as I can see real value in this. Imagine centralising all stdout and stderr from pods in combination with the analytics and trend identification capabilities from vRLI? Pretty interesting. Of course, we’re not that interested in what individual pods are logging, but if we have an example where some new code has been pushed out and 10’s / 100’s or 1000’s of pods start logging errors, we can identify, categorise and analyse these pretty easily with vRLI.

PKS and vRealize Log Insight in action

Talk is cheap, so let’s crack on.

Log into Ops Manager and select the PKS tile

Select “Logging” from the left and select “yes” under vRLI integration:

Enter the host and SSL settings where applicable in your environment:

Apply the changes:

if you keep an eye on the logs, references for the vRLI configuration will be shown:

– fluentd_vrli_ca_cert: “<redacted>”
– fluentd_vrli_host: “<redacted>”
+ fluentd_vrli_host: “<redacted>”
– fluentd_vrli_rate_limit_msec: “<redacted>”
+ fluentd_vrli_rate_limit_msec: “<redacted>”
– fluentd_vrli_skip_cert_verify: “<redacted>”
+ fluentd_vrli_skip_cert_verify: “<redacted>”
– fluentd_vrli_use_ssl: “<redacted>” + fluentd_vrli_use_ssl: “<redacted>”

Next, deploy a cluster in PKS:

After which, the following “hosts” can be observed, which in essence, is a reflection of the services within our Kubernetes cluster:

I also create a individual pod, named nginx-sleep. Below are the logs that were ingested for this event:

To validate the stdout capturing, create a cluster that writes to stdout:

And check the logs from the pod:

And also from Log Insight:

Conclusion

vRealize Log Insight provides a compelling platform for log ingestion, and it’s flexibility to ingest, analyse and interpret logs from physical, virtual and container based solutions makes it an extremely versatile tool in any admins repertoire.