Commit 5be0164c authored by Greg Sutcliffe's avatar Greg Sutcliffe

Final commit of all graphs, just text to go

parent 64bfc6ca
......@@ -90,13 +90,11 @@ down the multi-choice answers into seperate results, so the totals actually make
100% now. However, we do see a similar picture - strong preference for CentOS &
RHEL, backed up by Debian & Ubuntu. Nothing new here, I feel.
#### TODO support graphs and next work
```{r support}
print(support)
print(releases)
print(support)
```
as is the overall satisfaction with
the project - 78% of the community give us 4+ on this. Thanks for the positive
vibes, everyone!
......@@ -150,7 +148,7 @@ On the API front, we see more people using the API overall, but with less using
API v1 - I think we're getting close to finally dropping APIv1, yay!
```{r compute-resources}
grid.arrange(compute_resources_old,compute_resources,ncol=2)
grid.arrange(compute_resources_old,compute_resources,novnc_plot,ncol=3,widths=c(1,1,0.65))
```
Nothing too surprising here - bare metal is still king, VMware is the most
......@@ -162,7 +160,6 @@ providers to get CR plugins written quicker...
#### TODO - minor questions
##### Cronjobs
##### NoVNC console
### Monitoring
......@@ -170,7 +167,7 @@ A new question we asked about this year was around monitoring - whether you
monitor Foreman and it's hosts, and what you use to do that:
```{r monitoring}
grid.arrange(monitoring,monitor_foreman,ncol=2)
grid.arrange(monitoring,monitor_foreman,ncol=2,widths=c(1,0.5))
```
Some nice things to note here. Most people are monitoring hosts (`r 100 -
......@@ -190,14 +187,10 @@ Standalone => `r stdalone[stdalone$value == 'Only with Foreman',]$perc %>% round
features / plugins
```{r plugins}
grid.arrange(proxy_features,proxy_plugins,ncol=2)
```
puppet
```{r puppet}
print(proxy_puppet)
```{r proxies}
grid.arrange(num_proxies,proxy_puppet,ncol=2)
grid.arrange(proxy_features_old,proxy_features,ncol=2)
grid.arrange(proxy_plugins_old,proxy_plugins,ncol=2)
```
## Content
......@@ -207,7 +200,8 @@ manage-content: `r content[content$value == 'Yes',]$perc %>% round(2)`
solutions:
```{r manage-content}
grid.arrange(content_manage,content_types,repo_types,would_types,ncol=2)
grid.arrange(content_types,repo_types,ncol=2)
grid.arrange(content_manage,would_types,ncol=2)
```
note "local other" contains 3 votes for createrepo/yum, but largely is text like "my own scripts". Lack of "createrepo / yum" answers seems a win for Katello. GitLab seems mostly used as a Docker registry. Puppet answers were unclear, they could be "Puppet modules used to manage repos" or possibly "I manage Puppet modules as content".
......
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......@@ -79,10 +79,8 @@ down the multi-choice answers into seperate results, so the totals actually make
100% now. However, we do see a similar picture - strong preference for CentOS &
RHEL, backed up by Debian & Ubuntu. Nothing new here, I feel.
#### TODO support graphs and next work
![](InitialAnalysis_files/figure-html/support-1.svg)<!-- -->![](InitialAnalysis_files/figure-html/support-2.svg)<!-- -->
as is the overall satisfaction with
the project - 78% of the community give us 4+ on this. Thanks for the positive
vibes, everyone!
......@@ -142,7 +140,6 @@ providers to get CR plugins written quicker...
#### TODO - minor questions
##### Cronjobs
##### NoVNC console
### Monitoring
......@@ -151,7 +148,7 @@ monitor Foreman and it's hosts, and what you use to do that:
![](InitialAnalysis_files/figure-html/monitoring-1.svg)<!-- -->
Some nice things to note here. Most people are monitoring hosts (48.57%), but less than half are monitoring Foreman or the Proxies. We
Some nice things to note here. Most people are monitoring hosts (89.02%), but less than half are monitoring Foreman or the Proxies. We
should perhaps provide a blog post on what things should be monitored.
Looking at monitoring systems, there's lots of love for Zabbix and Nagios. The
......@@ -167,11 +164,7 @@ Standalone => 92.81
features / plugins
![](InitialAnalysis_files/figure-html/plugins-1.svg)<!-- -->
puppet
![](InitialAnalysis_files/figure-html/puppet-1.svg)<!-- -->
![](InitialAnalysis_files/figure-html/proxies-1.svg)<!-- -->![](InitialAnalysis_files/figure-html/proxies-2.svg)<!-- -->![](InitialAnalysis_files/figure-html/proxies-3.svg)<!-- -->
## Content
......@@ -179,7 +172,7 @@ manage-content: 63.52
solutions:
![](InitialAnalysis_files/figure-html/manage-content-1.svg)<!-- -->
![](InitialAnalysis_files/figure-html/manage-content-1.svg)<!-- -->![](InitialAnalysis_files/figure-html/manage-content-2.svg)<!-- -->
note "local other" contains 3 votes for createrepo/yum, but largely is text like "my own scripts". Lack of "createrepo / yum" answers seems a win for Katello. GitLab seems mostly used as a Docker registry. Puppet answers were unclear, they could be "Puppet modules used to manage repos" or possibly "I manage Puppet modules as content".
......
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......@@ -18,13 +18,13 @@ levels(data$howlong) <- c('3 months','6 months','1 year','2 years','3 years')
howlong_plot <- ggplot(data, aes(x = howlong, y = perc, fill = year)) +
geom_bar(stat = 'identity', position = 'dodge') +
labs(y = "Percent") +
ggtitle(" Time in community") +
ggtitle("Time in community") +
theme_grey() +
guides(color = 'legend') +
theme(legend.justification=c(0,1), legend.position=c(0,1)) +
theme(legend.title=element_blank()) +
theme(axis.title.x = element_blank()) +
theme(axis.title.y = element_blank()) +
theme(legend.background = element_rect(color = 'grey', size=0.2, linetype = 'solid') )
# Versions ----------------------------------------------------------------
......@@ -52,14 +52,14 @@ version_plot <- ggplot(data, aes(x = fct_relevel(version,'Older','Previous','Old
y = perc, fill = year, label = f)) +
geom_bar(stat = 'identity', position = 'dodge') +
geom_text(size = 3, position = position_dodge(width=1), vjust = -0.5) +
labs(y = "Percent") +
expand_limits(y=55) +
ggtitle(" Current Foreman version") +
ggtitle("Current Foreman version") +
theme_grey() +
guides(color = 'legend') +
theme(legend.justification=c(0,1), legend.position=c(0,1)) +
theme(legend.title=element_blank()) +
theme(axis.title.x = element_blank()) +
theme(axis.title.y = element_blank()) +
theme(legend.background = element_rect(color = 'grey', size=0.2, linetype = 'solid') )
......@@ -87,12 +87,11 @@ data <- rbind(
geo_plot <- ggplot(data, aes(x = f, y = perc, fill = year)) +
geom_bar(stat = 'identity', position = 'dodge') +
labs(y = "Percent") +
ggtitle(" Geographical Region") +
ggtitle("Geographical Region") +
theme_grey() +
guides(color = 'legend') +
theme(legend.justification=c(1,1), legend.position=c(1,1)) +
theme(legend.title=element_blank()) +
theme(axis.title.x = element_blank()) +
theme(legend.background = element_rect(color = 'grey', size=0.2, linetype = 'solid') ) +
theme(axis.text.x = element_text(angle=0, vjust=0.5))
\ No newline at end of file
theme(axis.title.y = element_blank()) +
theme(legend.background = element_rect(color = 'grey', size=0.2, linetype = 'solid') )
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......@@ -7,19 +7,58 @@ contribute = as_tibble(raw_csv$Do.you.contribute.to.Foreman.in.some.way.) %>%
ungroup() %>%
mutate(perc = n / sum(n)*100)
# Aware of ----------------------------------------------------------------
data = as_tibble(raw_csv$Are.you.aware.of.the.following.development.resources.) %>% filter(value != '')
c_aw = as.factor(unlist(strsplit(as.character(data$value),split = ";"))) %>%
fct_relabel(gsub, pattern=".*Option.*Demo.*", replacement="Present Demos") %>%
fct_relabel(gsub, pattern=".*Option.*Dive.*", replacement="Present Dives") %>%
fct_relabel(gsub, pattern=".*Community Demo.*", replacement="Watch Demos") %>%
fct_relabel(gsub, pattern=".*Deep Dives.*", replacement="Watch Dives") %>%
fct_relabel(gsub, pattern=".*handbook.*", replacement="Dev Handbook") %>%
fct_relabel(gsub, pattern=".*Wiki.*", replacement="Wiki") %>%
fct_count %>%
mutate(perc = n/sum(n)*100, year = '2018')
data = as_tibble(old_csv$Are.you.aware.of.the.following.development.resources.) %>% filter(value != '')
c_aw1 = as.factor(unlist(strsplit(as.character(data$value),split = ";"))) %>%
fct_relabel(gsub, pattern=".*Option.*Demo.*", replacement="Present Demos") %>%
fct_relabel(gsub, pattern=".*Option.*Dive.*", replacement="Present Dives") %>%
fct_relabel(gsub, pattern=".*Community Demo.*", replacement="Watch Demos") %>%
fct_relabel(gsub, pattern=".*Deep Dives.*", replacement="Watch Dives") %>%
fct_relabel(gsub, pattern=".*handbook.*", replacement="Dev Handbook") %>%
fct_relabel(gsub, pattern=".*Wiki.*", replacement="Wiki") %>%
fct_count %>%
mutate(perc = n/sum(n)*100, year = '2017')
data = rbind(c_aw,c_aw1)
contribute_aware = ggplot(data, aes(x = reorder(f, perc), y = perc, fill = year)) +
geom_bar(stat = 'identity', position = 'dodge') + coord_flip() +
labs(x = "", y = "Percent") +
ggtitle("Aware of ... (%)") +
theme_grey() +
guides(color = 'legend') +
theme(legend.justification=c(1,0), legend.position=c(1,0)) +
theme(axis.title.x = element_blank()) +
theme(axis.title.y = element_blank()) +
theme(legend.title=element_blank()) +
theme(legend.background = element_rect(color = 'grey', size=0.2, linetype = 'solid') )
# Contribute areas --------------------------------------------------------
data = raw_csv$What.areas.of.Foreman.do.you.currently.contribute.to..or.would.like.to.get.started.on.
c_a = as.factor(unlist(strsplit(as.character(data),split = ";"))) %>%
data = as_tibble(raw_csv$What.areas.of.Foreman.do.you.currently.contribute.to..or.would.like.to.get.started.on.) %>% filter(value != '')
c_a = as.factor(unlist(strsplit(as.character(data$value),split = ";"))) %>%
fct_lump(n=8) %>%
fct_count %>%
mutate(perc = n/sum(n)*100)
mutate(perc = n/sum(n)*100, year = '2018')
data = as_tibble(old_csv$What.areas.of.Foreman.do.you.currently.contribute.to..or.would.like.to.get.started.on.) %>% filter(value != '')
c_a1 = as.factor(unlist(strsplit(as.character(data$value),split = ";"))) %>%
fct_lump(n=8) %>%
fct_count %>%
mutate(perc = n/sum(n)*100, year ='2017')
data = rbind(c_a,c_a1)
contribute_areas = ggplot(c_a, aes(x = reorder(f, perc), y = perc, fill = f)) +
geom_bar(stat = 'identity') + coord_flip() +
labs(x = "", y = "Percent") +
scale_y_continuous(position = "top") +
contribute_areas = ggplot(data, aes(x = reorder(f, perc), y = perc, fill = year)) +
geom_bar(stat = 'identity', position = 'dodge') + coord_flip() +
scale_x_discrete(breaks=c("Packaging",
"Other",
"Translating",
......@@ -39,8 +78,13 @@ contribute_areas = ggplot(c_a, aes(x = reorder(f, perc), y = perc, fill = f)) +
"Unsure",
"Bugs")) +
ggtitle("Want to help with ... (%)") +
theme(legend.position = "none", axis.title.x = element_blank())
theme_grey() +
guides(color = 'legend') +
theme(legend.justification=c(1,0), legend.position=c(1,0)) +
theme(axis.title.x = element_blank()) +
theme(axis.title.y = element_blank()) +
theme(legend.title=element_blank()) +
theme(legend.background = element_rect(color = 'grey', size=0.2, linetype = 'solid') )
# Contribute Activities ---------------------------------------------------
......@@ -81,30 +125,10 @@ activities = ggplot(data,aes(x=fct_relevel(year,'2017','2018'),y=perc,label=year
facet_grid(. ~ type) +
labs(x = "", y = "Percent") +
ggtitle("Ease of ... (Rating == 4-5)") +
theme(legend.title = element_blank(),
legend.position = c(0.5,1.24),
legend.justification = c(0, 0),
legend.direction = 'horizontal',
legend.background = element_blank()
)
# Aware of ----------------------------------------------------------------
data = raw_csv$Are.you.aware.of.the.following.development.resources.
c_aw = as.factor(unlist(strsplit(as.character(data),split = ";"))) %>%
fct_relabel(gsub, pattern=".*Option.*Demo.*", replacement="Present Demos") %>%
fct_relabel(gsub, pattern=".*Option.*Dive.*", replacement="Present Dives") %>%
fct_relabel(gsub, pattern=".*Community Demo.*", replacement="Watch Demos") %>%
fct_relabel(gsub, pattern=".*Deep Dives.*", replacement="Watch Dives") %>%
fct_relabel(gsub, pattern=".*handbook*", replacement="Dev Handbook") %>%
fct_relabel(gsub, pattern=".*Wiki.*", replacement="Wiki") %>%
fct_count %>%
mutate(perc = n/sum(n)*100)
contribute_aware = ggplot(c_aw, aes(x = reorder(f, perc), y = perc, fill = f)) +
geom_bar(stat = 'identity') + coord_flip() +
labs(x = "", y = "Percent") +
ggtitle("Aware of ... (%)") +
scale_y_continuous(position = "top") +
theme(legend.position = "none", axis.title.x = element_blank())
theme_grey() +
guides(color = 'legend') +
theme(legend.justification=c(0,1), legend.position=c(0,1)) +
theme(axis.title.x = element_blank()) +
theme(axis.title.y = element_blank()) +
theme(legend.title=element_blank()) +
theme(legend.background = element_rect(color = 'grey', size=0.2, linetype = 'solid') )
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......@@ -28,13 +28,13 @@ data <- rbind(
hosts_plot <- ggplot(data, aes(x = fct_relevel(f,'0 - 9','10+','50+','200+','600+','1,000+','10,000+','20,000+'),
y = perc, fill = year)) +
geom_bar(stat = 'identity', position = 'dodge') +
labs(y = "Percent") +
ggtitle("Number of hosts ") +
ggtitle("Number of hosts") +
theme_grey() +
guides(color = 'legend') +
theme(legend.justification=c(1,1), legend.position=c(1,1)) +
theme(legend.title=element_blank()) +
theme(axis.title.x = element_blank()) +
theme(axis.title.y = element_blank()) +
theme(legend.background = element_rect(color = 'grey', size=0.2, linetype = 'solid') )
......@@ -52,7 +52,7 @@ data = rbind(
users_plot <- ggplot(data, aes(x = f, y = perc, fill = year)) +
geom_bar(stat = 'identity', position = 'dodge') +
ggtitle("Number of users ") +
ggtitle("Number of users") +
theme_grey() +
guides(color = 'legend') +
theme(legend.justification=c(1,1), legend.position=c(1,1)) +
......@@ -61,7 +61,6 @@ users_plot <- ggplot(data, aes(x = f, y = perc, fill = year)) +
theme(legend.title=element_blank()) +
theme(legend.background = element_rect(color = 'grey', size=0.2, linetype = 'solid') )
# OS choices --------------------------------------------------------------
# Foreman servers 2018
......@@ -130,12 +129,12 @@ os_plot <- ggplot(data, aes(x = fct_relevel(value,
'CentOS','RHEL','Fedora','Debian','Ubuntu','Oracle','SuSE','Windows','Other'),
y = perc, fill = year)) +
geom_bar(stat = 'identity', position = 'dodge') + facet_wrap(~type) +
labs(y = "Percent") +
ggtitle("Operating Systems used for ...") +
theme_grey() +
guides(color = 'legend') +
theme(legend.justification=c(1,1), legend.position=c(1,1)) +
theme(axis.title.x = element_blank()) +
theme(axis.title.y = element_blank()) +
theme(legend.title=element_blank()) +
theme(legend.background = element_rect(color = 'grey', size=0.2, linetype = 'solid') )
......@@ -165,8 +164,9 @@ hardware_plot <- ggplot(d2, aes(x = type, y = perc, label = perc,
geom_bar(stat = "identity", position = 'dodge') +
scale_fill_brewer(palette='RdYlGn') +
geom_text(aes(label = value), size = 3, position = position_dodge(0.9), vjust = -1.0) +
labs(y = "Percent") +
ggtitle("Hardware specifics") + expand_limits(y=100) +
ggtitle("Hardware specifics") +
expand_limits(y=100) +
theme_grey() +
theme(legend.position='none') +
theme(axis.title.x = element_blank())
\ No newline at end of file
theme(axis.title.x = element_blank()) +
theme(axis.title.y = element_blank())
\ No newline at end of file
# Monitor Hosts -----------------------------------------------------------
data = raw_csv$Do.you.also.monitor.Foreman.and.or.your.proxies.
data = as.factor(unlist(strsplit(as.character(data),split = ";"))) %>%
fct_count() %>%
......@@ -5,13 +7,17 @@ data = as.factor(unlist(strsplit(as.character(data),split = ";"))) %>%
monitor_foreman <- ggplot(data,aes(x = f, y = relative_perc, fill = f)) +
geom_bar(stat = 'identity') +
labs(x = "", y = "Percent") +
scale_x_discrete(breaks=c("I do monitor Foreman", "I do monitor my Proxies", "No, I don't monitor either"),
labels=c("Foreman", "Proxies", "Neither")) +
ggtitle("Also Monitor Foreman?") +
theme(legend.position = 'none')
theme_grey() +
guides(color = 'legend') +
theme(legend.position = 'none') +
theme(axis.title.x = element_blank()) +
theme(axis.title.y = element_blank())
# Monitoring systems ------------------------------------------------------
# types of monitoring for Hosts
data = raw_csv$Do.you.monitor.your.Foreman.managed.hosts. %>% fct_collapse(
"Other" = "",
"Nagios" = 'nagios and ganglia',
......@@ -21,13 +27,15 @@ data = raw_csv$Do.you.monitor.your.Foreman.managed.hosts. %>% fct_collapse(
CheckMK = c('check_mk', 'Check_MK', 'Check_mk', 'check_mk (nagios)', 'Check_MK+Nagios')) %>%
fct_lump(n=12) %>%
fct_count %>%
mutate(relative_perc = round((n / max(n))*100,2) )
mutate(relative_perc = round((n / length(raw_csv$Do.you.monitor.your.Foreman.managed.hosts.))*100,2) )
monitoring <- ggplot(data, aes(x = reorder(f,relative_perc), y = relative_perc, label = relative_perc, fill = f)) +
geom_bar(stat = 'identity', position = 'dodge') + coord_flip() +
# scale_fill_manual(values = cols1) +
labs(x = "", y = "Percent") +
ggtitle(paste("Monitoring Systems For Hosts")) +
theme_grey() +
guides(color = 'legend') +
theme(axis.title.x = element_blank()) +
theme(axis.title.y = element_blank()) +
theme(legend.position = "none")
not_monitor = data[data$f == "I don't monitor them",]$relative_perc
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