I completed my Master’s in computer science through Georgia Institute of Technology.   It took 3.5 years, and hundreds of hours each semester.   Normally I would take 2 classes per term.   Saying it was hard would be an understatement.   The hardest part are hours lost studying and away from my family.    It was like having a second full-time job.   I feel honored to be part of the 5th graduating class.   I’ve met some great people along the way.   Whether it was my first group in CS6310, only 3 of the original 5 made it thru that class.   The other group from CS8803 Cyber-Physical Design and Analysis who happened to be in the on-campus class.  I had the privilege to meet in person when I opened a retail store in Atlanta.   There were groups in other classes too.   The work taking a class two times to graduate.   

 I know the program is not meant to be easy, as the brainchild of and Dr. Zyi who will retire later this year.  He and faculty created something special, and the unbelievable amount work of my fellow students spent as TA’s.   I hope this program continues to educate the masses and continues to grow and develop.   I know it has made a positive impact on my life and hopefully, with time I’ll find ways to give back to the program.   

Every year 10s of thousands of AWS customers and prospect customers desend on Las Vegas. For those of us to don’t make the trek Amazon live streams the the daily Key Notes. Those are where AWS announces it’s newest products and changes. Each year I build a list before November as AWS has a tendency to leak smaller items. This year my wish list for AWS was as follows:

1. Mixing sizes and types in ASG - Announced
2. DNS fixed for Collapsed AD - Announced
3. Cross regional replication for Aurora PostGreSQL - Regions expanded  still waiting on the cross regions to be announced 
4. Lambda and more Lambda integrations  - Announced 
5. AWS Config adding machine learning based on account.  
6. Account level S3 bucket control - Partly Announced 
7. 40Gbps Direct Connect 

There a lot of announcements, far too many to recap if interested in them all go read the AWS News Blog.   I do like to find two announcements which shock me and two things that seem interesting. 

The two items which shocked me were:

1. DynamoDB added transactional support (ACID).   This means someone could build an e-commerce or banking application which requires consistent transactions on dynamoDB.  
2. AWS Outposts and AWS RDS on VMware allows you to deploy AWS on-premise and AWS will manage this for you.   I can only assume this is to help with migrations or workloads so sensitive they can’t move off-premise.     It would be interesting to see how AWS manages storage capacity and compute resources as many companies struggle with these and how the management model will work.   However, given the push to move away from traditional data centers, so reserves that course.   It will be interesting to see how it plays out over the next year and what services this provides a company migrating to the cloud. 

On my passions is security, so the two things which interested me are

• AWS Security Hub and  AWS Control Tower  - I consider these one thing as they will be used in tandem.   Control Center will provide security launch zone for an organization while AWS Security Hub will provide governance and monitoring of security 
• The ARM processor in the a1 instances which Amazon developed internally.   Based on pricing these instances seem to offer cost advantages to the existing instance types.   

What did you find interesting, amusing or shocking?   What were you looking for which wasn’t announced? 

I was listening to the Architech podcast.  There was a question asked, ”Does everything today tie back to Kubernetes?”   The more general version of the question is, “Does everything today tie back to containers?”.    The answer is quickly becoming yes.    Something Google figured out years ago with its environment that everything was containerized is becoming mainstream.

To support this  Amazon now has 3 different Container technologies and one in the works.

ECS which is Amazon’s first container offering.    ECS is container orchestration which supports Docker containers.    

Fairgate ECS which is managed offering of ECS where all you do is deploy Docker images and AWS owns full management.  More exciting is that  Fairgate for EKS has been announced and pending release.  This will be a fully managed Kubernetes.    

EKS is the latest offering which was GA’d in June.   This is a fully managed control plane for Kubernetes.   The worker nodes are EC2 instances you manage, which can run an Amazon Linux AMI or one you create.

Lately, I’ve been exploring EKS so that will be the next blog article, how to get started on EKS.

In the meantime, what have you containerized today?

A new study sponsored by Capsule8, Duo Security, and Signal Sciences was published about Cloud Native Application Security.   Cloud Native Applications are applications specifically built for the Cloud.  The study entitled,  The State of Cloud Native Security.  The observations and conclusions of the survey are interesting.   What was surprising is the complete lack of discussion of moving the traditional SECOPS to a SecDevOps model.  

The other item, which found shocking with all the recent breaches, that page 22 shows that only  71% of the surveyed companies have a SECOPs function. 

Open source has been around for decades, but the real initiatives started in 1998. Due to some recent experiences, I started pondering open source and the future of software.

I believe the future of software is open source where a company which wraps enterprise support around it.

Take any open source software,  if you need a feature typically someone has built it.  If they haven’t, your team ends up creating it and adding it back to the project.    Open source has the power of community vs a company with a product manager and deadlines to ship based on some roadmap built by committee.  I made it too simple, open source has a product manager, really in most communities they are gate keeper.   They own accepting features and setting direction,  in some cases it’s the original developer like Linux, or sometimes it’s a committee,  However, at the end of the day either commercial or open source has a product owner.

It’s an interesting paradux which created two opposing questions. First, why isn’t all software open sourced?   Why would a company who has spent millions In development going to give the software away and charge for services?

The answer to the first question is see question two.  The answer to the second question is giving away software is not financially viable if millions have been invested unless a robust software support model is supporting the development of software.

I worked for many organizations who’s IT budget was lean and agile,   Open source was was minimal budget dollars.  I have worked for other organizations whose budget is exceptionally robust and requires supported software as part of governance.

Why not replace the license model with a support model, and allow me or even more importantly the community access to the source code, contribute and drive innovation. Based on users, revenue or some other metric charge me for support or allow me to opt out. Seems like a reasonable future to me.

Amazon recently released a presentation on Data-safe Cloud.  It appears to be based on some Gartner question and other data AWS collected.  The presentation discusses 6 core benefits of a secure cloud.

1. Inherit Strong Security and Compliance Controls
2. Scale with Enhanced Visibility and Control
3. Protect Your Privacy and Data
4. Find Trusted Security Partners and Solutions
5. Use Automation to Improve Security and Save Time
6. Continually Improve with Security Features.  

I find this marketing material to be confusing at best, let’s analyze what it is saying. 

For point 1, Inherit Strong and Compliance Controls, which reference all the compliance AWS achieves.  However, it loses track of the shared responsibility model and doesn’t even mention until page 16.   Amazon has compliance in place which is exceptional, and most data center operators or SaaS providers struggle to achieve.   This does not mean my data or services running within the Amazon environment meet those compliances

For point 2,  4  and 6 those are not benefits of the secure cloud.  Those might be high-level objects one uses to form a strategy on how to get to a secure cloud.  

Point 3 I don’t even understand, the protection of privacy and data has to be the number one concern when building out workloads in the cloud or private data centers.   It’s not a benefit of the secure cloud, but a requirement.  

For point 5, I am a big fan of automation and automating everything.   Again this is not a benefit of a secure cloud, but how to have a repeatable, secure process wrapped in automation which leads to a secure cloud.

Given the discussions around cloud and security given all the negative press, including the recent AWS S3 Godaddy Bucket exposure, Amazon should be publishing better content to help move forward the security discussion.  

One of the things I’ve been fascinated of late is the concept of Security as Code.   I’ve just started to read the book DevOpSec by Jim Bird.   One of the things the book talks about is injecting security into the CI/CD pipeline for applications.  Basically merging developers and security, as DevOps merged developers and operations.   I’ve argued for years DevOps is a lot of things, but fundamentally it was a way for operations to become part of the development process which led to the automation of routine operational tasks and recovery.  So now if we look at DevOpsSec, this would assume security is part of the development process. I mean more than just the standard code analysis using Veracode.  What would it mean if security processes and recovery could be automated?  

Security Operations Centers (SOCs) where people are interpreting security events and reacting.  Over the last few years, much of the improvements in SOCs has been made via AI and machine learning reducing the head count required to operate a SOC.   What if security operations were automated?   Could some code be generated based on the security triggers and provided to the developer for review and incorporation into the next release?

We talk about infrastructure as code, where some data can be generated to create rules and infrastructure using automation.   Obviously on AWS you can install security tool based AMIs, Security Groups and NACLs with Cloudformation.  My thoughts go to firewall based AMIs, appliances  for external access.   The appliance access-lists required are complex, require enormous review and processing within an organization.  Could access lists be constructed based on a mapping of the code and automatically generated for review?  Could the generated access list be compared against existing access-list for deduplication detection.

It’s definitely an interesting topic and hopefully evolves over the next few years. 

Amazon generates a lot of logs via VPC Flow Logs, CloudTrail, S3 access logs, CloudWatch (See the end of the blog article for a full list.)   Additionally, there are OS, Application, web server logs.   That is a lot of data which provides valuable insight into your running AWS environment.   What are you doing to manage this log files?  What are you doing with those log files?  What are you doing to analysis these log files?

There are a lot of logging solutions available that integrate with AWS. Honestly, I’m a big fan of Splunk and have set it up multiple times.  However, I wanted to look at something else for this blog article. Something open source and relatively low cost. This blog is going to explain what I did to setup Graylog. Graylog has no charges for the software, but you’re going to get charged for the instance, Kinesis, SQS, and data storage.  It actually a good exercise if to familiarize yourself with AWS services, especially for the Sysops exams.  

Graylog provides great instructions.   I followed the steps remember to use their image which is already self-built on Ubuntu.   One difference with this setup, I didn’t use a 4GB memory systems.   I picked a t2.small which proves 1vCPU and 2GB of memory.    I didn’t notice performance issues.  Remember to allow ports 443 and 9000 in security groups and the Networking ACLs.   I prefer to run this over HTTPS.  And it bugs me when you see NOT SECURE HTTP:  I installed an SSL certificate, and this is how I did it.

1. Create a DNS name 
2. Get a free certificate 
3. Install the Certificate as such 

Now my instance is up, and I can log into the console.  I want to get my AWS logs into Graylog.   To do this is requires the logs sent to Kinesis or SQS.  I am not going to explain the SQS setup as there plenty of resources for the specific AWS Service.   Also, the Graylog Plugin describes how to do this.  Graylog plugin for CloudTrail, CloudWatch and VPC Flow logs is available on Github at Graylog Plugin for AWS.

What about access_logs?  Graylog has the Graylog Collector Sidecar.      I’m not going to rehash the installation instructions here as there are great installation instructions.     Graylog has a great documentation.   Also if you are looking for something not covered here, it will be in the documentation or in their Github project. 

What are you using as your log collection processing service on Amazon?  

List of AWS Servers generating logs:

Amazon S3 Access logs Amazon CloudFront Access logs Elastic Load Balancer (ELB) logs Amazon Relational Database Service (RDS) logs Amazon Elastic MapReduce (EMR) logs Amazon Redshift logs AWS Elastic Beanstalk logs AWS OpsWorks logs (or this link) AWS Import/Export logs AWS Data Pipeline logs AWS CloudTrail logs

A longtime issue with networking vendors is providing ports at one speed and the throughput at another speed.  I remember dealing with it back in 2005 with the first generation of Cisco ASA’s which primarily replaced the PIX Firewall.   Those firewalls provided 1Gbps ports, but the throughput the ASA could handle was about half that bandwidth.

Some marketing genius created the term wire speed and throughput.

If you’re curious about this go look at Cisco Firepower NGFW firewalls.  The 4100 series have 40Gbps interfaces, but depending on the model throughput is between 10Gbps and 24Gbps with FW+AVC+IPS turned on.

I have referenced several  Cisco devices, but it’s not a specific issue to Cisco.    Take a look at Palo Alto Networks Firewalls specifically the PA-52XX have four 40Gbps ports, but can support between 9Gbps and 30Gbps of throughput with full threat protection on.

The technology exists so why aren’t networking vendors able to provide wire-speed throughput between ports, even with the full inspection of traffic turned on?    I would very like to know your thoughts on this topic please leave a comment.

Starting a new position today as Consultant - Cloud Architect with Taos.   Super excited to for this opportunity.

I wanted a position as a solution architect working with the Cloud, so I couldn’t be more thrilled with the role.   I am looking forward to helping Taos customers adopt the cloud and a Cloud First Strategy.

It’s an amazing journey for me, as Taos was the first to offer me a Unix System administrator position when I graduated from Penn State some 18 years ago, and I passed on the offer and went to work for IBM.

I am really looking forward to working with the great people at Taos.

Remember back in the 1990s/2000s Data Warehouses were all the rage.    The idea was to take data from all the transactional databases behind the multiple e-Commerce, CRM, financials, lead generation and ERP systems deployed in the company and merge them into one data platform.  It was the dream, CIOs were ponying up big dollars for these because they thought it would solve finance, sales, and marketing most significant problems.  It was even termed Enterprise Data Warehouse or EDW.  The new EDW would take 18 months to deploy as ETLs would be written from the various systems and data would have to be normalized to work within the EDW.  In some cases, the team made bad decisions about how to normalize the data causing all types of future issues.   When the project finished, there would be this beautiful new data warehouse, and no one would be using it.  The EDW needed a report writer, to make fancy reports, in a specialized tool like Cognos, Crystal Reports, Hyperion, SAS, etc.   A meeting would be called to discuss data, with 12 people and all 12 people would have different reports and numbers depending on the formulas in the report.  That lead to eventually someone from Finance who was part of the analysis, budgeting and forecasting group would learn the tool and be the go-to person and work with the team from technology assigned to create reports.

Then Big Data came along. Big data even sounds better than Enterprise Data Warehouse, and frankly given the issues back in 1990s/2000s the branding to Big Data doesn’t have the same negative connotations.

Big Data isn’t a silver bullet, but it does a lot of things right.  First and foremost the data doesn’t require normalization.  Actually normalization is discouraged.  Big Data absorbs the transactional database data, social feeds, eCommerce analytics, IoT sensor data, and a whole host of other data and puts it all in one data repository. The person from finance has been replaced with a team of data scientists who are highly trained and develop analysis models and extracts data with statistical (R programming language) and Natural Language Processing (NLP). The data scientists spend days pouring over the data, extracting information, building models, rebuilding models and looking for patterns within the data. The data could be text, voice, video, images, social feeds, transaction data and the data scientist is looking for something interesting.

Big Data has huge impacts as the benefits are immense.  However, my favorite is predictive analytics.  Predictive analytics tells you something’s behavior based on previous history and current data. It’s going to predict the future.  Predictive analysis is all over retail as you see it on sites as “Other Customers Bought” or recommending purchases based on your history.   Airlines use it to predict component failure of planes.  Investors use it to predict changes in stock, and the list of industries using it goes on and on.

The cloud is a huge player in the Big Data space Amazon, Google and Azure are offering Hadoop and Spark as services.    The best thing about the cloud is when the data is absorbed in Gigabytes or Terabytes that the cloud is providing the storage space for all this data.  Lastly given it’s in the cloud, it’s relatively easy to deploy a Big Data cluster, and hopefully,  soon AI in the cloud will replace the data scientists as well.

Studying for the CCNP Route 300-101 Route exam, there is no discussion of Border Gateway Protocol(BGP) Route Reflectors.    It doesn’t even make the exam blueprint.  BGP Route Reflectors are one of the most important elements for multi-home, multi-location BGP.    This blog post is not going to be a lesson in BGP, as there are plenty of resources do a great job explaining the topic.   Within an Autonomous system(AS) if there are multiple BGP routers, an iBGP full mesh is required.   Its a fancy way of saying all the BGP routers need to be connected within an AS.  Let’s take an example of a large company which has Internet peering in New York, Atlanta and San Francisco.   If the large company is the same AS number, that means it has at least 3 BGP routers, and for business reasons, the routers are dual and dual homed.   That makes 6 BGP routers.  Remember the formula for a full mesh is: N(N-1)/2.   Based on the formula, it would require 15 iBGP peering connections.  iBGP makes a logical connection over TCP, but it still needs 15 configurations.   This is a small example, but it doesn’t scale if we increased to 10 routers, that means 45 iBGP connections and configurations.

What does a route reflector do?

A Route Reflector readvertise routes learn from internal peers to other internal peers.   Only the route reflector needs a full mesh with its internal routers.  The elegance of this solution is that it is a way of making iBGP hierarchical.

The previous example of 6 routers, there are many ways to organize the network with Router Reflectors.   One Cluster with two route reflectors, two clusters with two route reflectors, etc.

 The astonishing part is something so fundamental to leveraging BGP is not cover on the CCNP Routing Exam according to the exam blueprint.

IPv4 exhaustion is technology’s version of chicken little and sky is failing.     The sky has been falling on this for 20+ years, as we have been warned IPv4 is exhausting since the late 1990s.   Here comes the IoT including Smart Home were supposed to strain the IPv4 space.    I don’t know about you, but I don’t want my refrigerate and smart thermostat on the internet.

However, every time I go into AWS, I can generate an IPv4 address.   Home ISP are stilling handing out static IPv4 if you are willing to pay a monthly fee.     Enterprise ISP will hand you a /28 or /29 block without to much effort.    Sure lots of companies, AWS, Google, Microsoft have properties on IPv6.   But it’s not widely adopted.   The original RFC on IPv6 was published in December of 1995.

I believe the lack of adaption is due to the complexity of the address. If my refrigerators IPv4 address is 192.168.0.33.    It’s IPv6 address is 2001:AAB4:0000:0000:0000:0000:1010:FE01 which could be shorten to  2001:AAB4::1010:FE01.   Imagine calling that into tech support or being tech support taking that call.  Why didn’t the inventors of IPv6 add octets to the existing IP address?   For instance, the address 192.168.0.33.5.101.49, would have been so much more elegant and easier to understand.     I think it will take another 15-20 years before IPv6 is widely adapted and another 50 years before IPv4 is no longer routed within networks.

I was having a conversation with an old colleague late Friday afternoon.    (Friday was a day of former colleagues, had lunch with a great mentor).   He’s responsible for infrastructure and operations for a good size company.    His team is embarking on a project to migrate to the cloud as their contract for space will be up in 2020. There three things which were interesting in the discussion which I thought were interesting and probably the same issues others face on their journey to the cloud.

The first was the concern about security.    The cloud is no less or more secure than your data center. If your data center is private your cloud asset can be private, if your need public facing services, they would be secured like the public facing services in your own data center.    Data security is your responsibility in the cloud, but the cloud doesn’t make your data any less secure.

The other concern was the movement of VMware images to the cloud.   Most of the environment was virtualized years ago.   However, there are a lot of windows 2003 and 2008 servers.    Windows 2008  end of support is  2020, and Windows 2003 has been out of support since July 2015.     It’s odd the concern about security, given the age of the Windows environment.      If it was my world, I’d probably figure out how to move those servers to Windows 2016 or retire ones no longer needed, keeping in mind OS upgrades are always dependent on the applications.   Right or wrong, my roadmap would leave Windows 2003 and 2008 in whatever datacenter facility is left behind.

Lastly, there was concern about Serverless, and the application teams wanting to leverage this over his group’s infrastructure services.   There was real concern about a loss of resources if the application teams turn towards Serverless, as his organization would have fewer servers (physical/virtual instances)  to support.  Like many technology shops, infrastructure and operations resources are formulated by the total number of servers.   I find this hugely exciting.    I would push resources from “keeping the lights on” to roles focused on growing the business and speed to market, which are the most significant benefit of serverless.   Based on this discussion, people look at it from their own prism.

There hundreds of note taking apps.    My favorites are Evernote, GoodNotes, and Quip.   I’m not going to get into the benefits or pros and cons of each application.  There plenty of BLOGs, youtube videos which do this in great detail.    Here is how I used them:

• Evernote is my document and note repository.

• GoodNotes is for taking handwritten notes on my iPad, and the PDFs are loaded into Evernote.

• Quip is for team collaboration and sharing notes and documents.

I’ve been digital for 4+ years.  Today, I read an ebook from Microsoft, entitled “The Innovator’s Guide to Modern Note Taking.“  I was curious as to Microsoft’s ideas on the digital note-taking.   The ebook is worth a read.    I found there three big takeaways from the ebook:

First - The ebook quotes, “average employee spends 76 hours a year looking for misplaced notes, items, and files.   In other words, we spend annual $177 billion across the U.S”.

Second - The ebook explains that the left side of the brain is used when typing on a keyboard,  and the right side of the brain is when writing notes.  The left side of the brain is more clinical, and the right side of the brain is more creative, particular asking the “What If” questions.  Also covered on page 12 of the ebook handwriting notes improves retention.  Lastly on page 13 one of my favorites as I am a doodler, “Doodlers recall on average 29% more information than non-doodlers”.   There is a substantial difference in typing vs. writing notes, and there is a great blog article from NPR if you want to learn more.

_Third - _Leverage the cloud, whether it’s to share, process, access anywhere.

Those are fundamentally the three reasons that I went all digital for notes.  As described before I write notes in GoodNotes and put them in Evernote, I use the Evernote OCR for PDFs to search them.    My workflow covers the main points described above.   Makes me think I might be ahead of a coming trend.

I believe that Multi-cloud environments are going to be the most important technology investment in 2018/2019.   This will drive education and new skill development among various technology workers.  Apparently, it’s not just me, IDC prediction is that “More than 85% of Enterprise IT Organizations Will Commit to Multicloud Architectures by 2018, Driving up the Rate and Pace of Change in IT Organizations”.There some great resources online for multi-cloud, strategy, benefits, all worth reading:

• IBM’s multi-cloud

• I-SCOOP

• DataCenter Knowledge 

• RightScale 2018 State of the Cloud Report

• NewRelic - Making Multi-Cloud Environments…

The list could be hundreds of articles.   I wanted to provide a few, that I thought were interesting and relevant to this discussion of why Multi-cloud.   There are four drivers behind this trend:

First -  Containers will allow you to deploy your application anywhere, including all the major cloud players have Kubernetes, Docker support.    This means you could deploy to AWS, Azure, and Google without rewriting any code.    Application support, development, maintenance is what drives technology dollars.   Maintaining one set of code that runs anywhere doesn’t cost any more and gives you complete autonomy.

Second -  Companies like Joyent,  Netlify,  HashiCorp Terraform and many more are building their solutions for multi-cloud, giving the control, manageability, ease of use, etc.    Technology is like Field of Dreams, quote, “if you build it they will come.”   Very few large companies jump into something without support, they wait for some level of maturity to be developed and then wade in slowly.

Third -  The biggest reason is a lack of trust putting all your technology assets into one company.    Most companies had for years multi-data center strategies, using a combination of self-created, leverage multiple companies like  Wipro, IBM, HP, Digital Realty Trust, etc., and various co-location.   For big companies when the cloud became popular, it was how do I augment my existing environment with Cloud.    Now many companies are applying a Cloud First Strategy .    So why wouldn’t principles that were applied for decades in technology, be applied to the cloud.   Everyone remembers the saying, don’t put all your eggs in one basket.    I understand there are regions, multi-AZ, resiliency, and redundancy, but at the end of the day one cloud provider is one cloud provider, and all my technology eggs are in that one basket.

Fourth - The last reason is pricing.   If you can move your entire workload from Amazon to Google within minutes, it forces cloud vendors to keep costs low as cloud service charges for what you use.   I understand if you have a workload with petabytes of data, it’s not going to move.  But have web services with small data behind them, they can move and relatively quickly with the right deployment tools in place.

What do you think?   Leave me a comment with your feedback or ideas?

Amazon is crashing on Prime Day,  made breaking news.   Appears the company is having issues with the traffic load.

Given Amazon runs from AWS as of 2011. Not a great sign for either Amazon or the scalability model they deployed on AWS.

Why do agencies post minimum security standards?     The UK government recently released a minimum security standards document which all departments must meet or exceed.    The document is available here:  Minimum Cyber Security Standard.

The document is concise, short, and clear.   It contains some relevant items for decent security, covering most common practices over the last 10 years.   I’m not a UK citizen, but if agencies are protecting my data, why do they have to meet minimum standards.    If an insurer was using the minimum standards, it would be “lowest acceptable criteria that a risk must meet in order to be insured”.     Do I really want to be in that class lowest acceptable criteria for a risk to my data and privacy?

Given now, you know government agencies apply minimum standards, let’s look at breach data.   Breaches are becoming more common and more expensive and this is confirmed by a report from Ponemon Institue commissioned by IBM.   The report states that a Breach will cost $3.86 million, and the kicker is that there is a recurrence 27.8% of the time.

There two other figures in this report that astound me:

• The mean time to identify (MTTI) was 197 days

• The mean time to contain (MTTC) was 69 days

That means that after a company is breached, it takes on average 6 months to identify the breach and 2 months to contain it.   The report goes on to say that 27% of the time a breach is due to human error and 25% of the time because of a system glitch.

So interpolate this, someone or system makes a mistake and it takes 6 months to identify and 2 months to contain.    Those numbers should be scaring every CISO, CIO, CTO, other executives, security architects, as the biggest security threats are people and systems working for the company.

Maybe it’s time to move away from minimum standards and start forcing agencies and companies to adhere to a set of best practices for data security?

I see a lot of trends between Containers in 2018 and the server virtualization movement started in 2001 with VMWare.  So I started taking a trip down memory lane.  My history started in 2003/2004 when I was leveraging Virtualization for datacenter and server consolation. At IBM we were pushing it to consolidate unused server capacity especially in test and development environments with IT leadership.  The delivery primary focused on VMWare GSX and local storage initially.  I recall the release of vMotion and additional Storage Virtualization tools, lead to a deserve to move from local storage to SAN-based storage.   That allowed us to discuss the reduction of downtime and potential for production deployments.  I also remember there was much buzz when EMC in 2004 acquired VMWare and it made sense given the push into Storage Virtualization.

Back then it was the promise of reduced cost, smaller data center footprint, improved development environments, and better resource utilization.   Sounds like the promises of Cloud and Containers today.

Serverless is becoming the 2018 technology hype.   I remember when containers were gaining traction in 2012, and Docker in 2013.  At technology conventions, all the cool developers were using containers.   It solved a lot of challenges, but it was not a silver bullet. (But that’s a blog article for another day.)

Today after an interview I was asking myself,  have Containers lived up to the hype?   They are great for CI/CD, getting rid of system administrator bottlenecks, helping with rapid deployment, and some would argue fundamental to DevOps.  So I started researching the hype.   People over at  Cloud Foundry published a container report in  2017 and 2016.

Per the 2016 report, “our survey, a majority of companies (53%) had either deployed (22%) or were in the process of evaluating (31%) containers.”

Per the 2017 report, “increase of 14 points among users and evaluators for a total of 67 percent using  (25%) or evaluating (42%).”

As a former technology VP/director/manager, I was always evaluating technology which had some potential to save costs, improve processes, speed development and improve production deployments.   But a 25% adaption rate and a 3% uptick over last year, is not moving the technology needle.

However, I am starting to see the same trend, Serverless is the new exciting technology which is going to solve the development challenges, save costs, improve the development process and you are cool if you’re using it.       But is it really Serverless or just a simpler way to use a container?

AWS Lambda is basically a container.  (Another blog article will dig into the underpinnings of Lambda.)   Where does the container run? ** A Server. **

Just means I don’t have to understand the underlying container, server etc.etc.etc.     So is it truly serverless?   Or is it just the 2018 technology hype to get all us development geeks excited, we don’t need to learn Docker or Kubernetes, or ask our Sysadmin friends provision us another server.

Let me know your thoughts.

I had a goal 4 weeks ago, to pass 5 AWS certifications in 4 weeks.      I completed this goal:

• AWS Certified Solutions Architect – Associate

• AWS Certified Developer – Associate

• AWS Certified SysOps Administrator – Associate

• AWS Certified Advanced Networking – Specialty

• AWS Certified Solutions Architect – Professional

For the time being,  I’m going to be done with AWS certifications, unless I get a position which leverages AWS.      This week I made a list of the certifications that I will look at over the coming year with a goal to complete all of them by August of 2019.    I still have a fall semester to finish, so I’ll stop certifications at the end of August until December to focus on finishing my masters.

The list of Certifications I made.

• Azure

• GCP

• CISSP

• CISM

• Cisco

  • CCNA

  • CCDA

  • CCNP

  • CCDP

• TOGAF

• ITIL

• Linux Certification

Anyone know of any other ones to pursue?    Think it’s a good list for a Solution Architect as it has a broad range of cloud technologies, networking, and security.

I have decided, that my next challenge will be 2 Cisco Certifications in the next 2 weeks.     After that, we’ll see what is next on the list.

Is DevOps the most overused word in technology right now?

The full definition from Wikipedia.  Here what DevOps really is about.   It about taking monolithic code with complex infrastructure supported by developers, operational personnel, testers, system administrators and simplifying it, monitoring it and taking automated corrective actions or notification.

It’s really about reducing resources who aren’t helping the business grow and using that headcount toward a position which can help revenue growth.

It’s done in 3 pieces.

Piece 1. The Infrastructure

It starts by simplifying the infrastructure build-out, whether it in the cloud where environments can be spun up and down instantly based on some known configuration like AWS CloudFormation,  using Docker or Kubernettes.   Recently, Function as a Service (FaaS), AWS Lambda,  Google Cloud Functions or Azure Functions. This reduces reliance on a DBA, Unix or Windows System Administrator and Network Engineers.   Now the developer has the space they need instantly.   The developer can deploy their code quicker, which speeds time to market.

Piece 2.  Re-use and Buy vs. Build

Piece 2 of this is the Re-use and Buy vs. Build.   Meaning if someone has a service re-use it, don’t go building your own.    An example is Auth0 for authentication and Google Maps for mapping locations or directions.

Piece 3.  When building or creating software do it as Microservices.

To simplify it you are going to implement microservices.   Basically, you create code that does one thing well.  It’s small, efficient and manageable.    It outputs JSON which can be parsed by upstream Services.   The JSON can extend without causing issues to upstream Services.   This now reduces the size of the code base a developer is touching, as it one service.   It reduces regression testing footprint.      So now the number of testers, unit tests, regression tests and integration tests have been shrunk.   This means faster releases to production, and also means a reduction in resources.

You’re not doing DevOps if any of these conditions apply?

1. You have monolithic software you’ve put some web services in front of.

2. Developers are still asking to provision environments to work.

3. People are still doing capacity planning and analysis.

4. NewRelic (or any other system)  is monitoring the environment, but no one is aware of what is happening.

5. Production pushes happen at most once a month because of the effort and amount of things which break.

Doing DevOps

1. Take the monolithic software and break it into web services.

2. Developers can provision environments per a Service Catalog as required.

3. Automate capacity analysis.

4. Automatic SLAs which trigger notifications and tickets.

5. NewRelic is monitoring the environment, and it providing data to systems which are self-correcting issues, and there are feedback loops on releases.

6. Consistently (multiple times a week)  pushing to production to enhance the customer experience.

What’s up with interviewers asking about kubernetes experience lately?   Two different interviewers raised the question today.

Kubernetes Is only 4 years old .   GCP has supported it for a while. AWS released it in beta at Re:invent 2017 and it went general release June 5 2018.   Azure went GA June 13, 2018.

So how widely deployed is it?     Also if it is supposed to speed deployments, how complex can it be?   How many hours to learn it?

Next week I will be learning it.  Looking forward to answering these questions.