MacOS Docker Installation problems?

If after a docker installation on your mac you are getting something like:

Get http:///var/run/docker.sock/v1.20/version: dial unix /var/run/docker.sock: no such file or directory.
* Are you trying to connect to a TLS-enabled daemon without TLS?
* Is your docker daemon up and running?

You came to the right place.

If you follow the steps from official tutorial on how to install docker on Mac, you will come to a point where you can’t run docker. It took me a good chunk of time to find the solution so I’ve decided to write this short post on it. I hope it will be fixed soon as for this issue – but for now you will need to follow these 3 steps:

2014 Summary

2014 was a busy year.
In few moments of reflection, it feels more like 3-4 years. Anyway, let’s try to see where was the interesting stuff on this blog.

The Web

• New projects’ site
  After two years, I’ve decided to go with a little ‘makeover’ to the site. It’s still work in progress, but we can see the improvement so the trend is good.
  
  
  
• Top Posts
  • Yahoo finance hidden API – It’s an old post, but I guess people are still looking for ways to get fresh finance data.
  • Debug NodeJS like a pro – NodeJS ecosystem keep coming to this one. It’s still not trivial, but the solution in the post give you an easy option to debug your JavaScript code on the server-side.
  • Chrome OS
    • How to prevent your Chromebook from going to sleep
    • Install ChromiumOs on your old laptop
    • How to make your Chromebook even faster
  • How to use indexed DB simplest

 

Google Cloud: Managed VMs And Docker

“Google’s ability to build, organize, and operate a huge network of servers and fiber-optic cables with an efficiency and speed that rocks physics on its heels. This is what makes Google Google: its physical network, its thousands of fiber miles, and those many thousands of servers that, in aggregate, add up to the mother of all clouds.” – Wired
This quote about Google cloud platform is on the spot. In the slides below,  I tried to give an overview on the new features that are now part of Google cloud. If you attended #CodeMotion TLV yesterday – You will find these slides familiar. If it’s not the first time you hear the phrase ‘Google cloud’, jump to slide 14.

Upload Data To BigQuery With A Smile

What is BigQuery?

In our world of ‘Big Data’ it can be time consuming and expensive to query massive datasets without the right infrastructure. Google BigQuery solves this problem by enabling super-fast, SQL-like queries against append-only tables, using the processing power of Google’s infrastructure.

What You need to do?

1. Move your data into BigQuery – This is what we will do in this post.
2. Let Google BigQuery handle the hard work.
3. Query your big data with a smile in this cost/effective way.

How to upload data to Big Query?

There are two main approaches: stream you data or upload it directly from Google cloud storage. Let’s have a look at the steps to leverage Google cloud storage in order to upload data into BigQuery.

The main steps you need to follow:

1. You will need to prepare your data. In this stage, you need to analyze and think what will be the best format (both JSON and CSV are supported).
2. In our example, we will show you how to work with CSV files and even better, we will upload them to Google Cloud Storage and later with a BigQuery job we will make sure our data is being pulled automatically into BigQuery.
3. Run a ‘sanity’ check to see that the new data is in good shape (optional step).

Tips

• Upload your the data to a project with a good name (The default project names are not too clear in most cases).
• Consider breaking your data (e.g monthly tables instead of a unique big one) because it will make life easier in the future to update, query and maintain the data source.
• Have an example dataset with data that reflect the popular cases. This could be great to give developer an option to ‘play’ with the data and see its value.
• Think on some good and bold example. A few sample queries are crucial to get people started on a dataset.

What’s New In Google Developers World

Here are my slides from a talk I gave last week on what’s new and available for you as a developer in Google’s world. This talk gives a high level overview on the main APIs. If you wish to dive deeper on some of them, you will find many links in the slides.

Big Query Basics

In today talk, I’ve covered one of the coolest tools in the “big data” world – Big Query. What is BigQuery? Well, querying massive datasets can be time consuming and expensive without the right hardware and infrastructure. BigQuery solves this problem by enabling super-fast, SQL-like queries, using the processing power of Google’s infrastructure. If you wish to play with a cool a BQ demo, just click on the picture on the left.

When to use it?

There are few bold use cases in the analytic landscape that Big Query is the right tool for the job:

• It’s a great option when your MapReduce based analysis (=Hadoop system) can be slow for ad-hoc queries.
• If you don’t wish to manage large data centers and tuning Hadoop all day long.
• It seems that analytics tools should be services at 2014, no?

Google Cloud Storage Migration, Backup, and Archive

Today we covered Google Cloud Storage. Google Cloud Storage is a RESTful service for storing and accessing your data objects on Google’s infrastructure. Few important features: Multiple layers of redundancy. All data replicated to multiple data centers. Objects can be terabytes in size, with resumable uploads and downloads, and range read support. If you wish to start with Google cloud storage, a good starting point will be to click on the image to the left. In my session, I’ve covered:

• Migrating Data to Cloud Storage
• Object Composition
• Durable Reduced Availability Storage